ChunkTokenizer

Companion object ChunkTokenizer

class ChunkTokenizer extends Tokenizer

Tokenizes and flattens extracted NER chunks.

The ChunkTokenizer will split the extracted NER CHUNK type Annotations and will create TOKEN type Annotations. The result is then flattened, resulting in a single array.

For extended examples of usage, see the ChunkTokenizerTestSpec.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.{ChunkTokenizer, TextMatcher, Tokenizer}
import com.johnsnowlabs.nlp.annotators.sbd.pragmatic.SentenceDetector
import com.johnsnowlabs.nlp.util.io.ReadAs
import org.apache.spark.ml.Pipeline

val documentAssembler = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("document")

val sentenceDetector = new SentenceDetector()
  .setInputCols(Array("document"))
  .setOutputCol("sentence")

val tokenizer = new Tokenizer()
  .setInputCols(Array("sentence"))
  .setOutputCol("token")

val entityExtractor = new TextMatcher()
  .setInputCols("sentence", "token")
  .setEntities("src/test/resources/entity-extractor/test-chunks.txt", ReadAs.TEXT)
  .setOutputCol("entity")

val chunkTokenizer = new ChunkTokenizer()
  .setInputCols("entity")
  .setOutputCol("chunk_token")

val pipeline = new Pipeline().setStages(Array(
    documentAssembler,
    sentenceDetector,
    tokenizer,
    entityExtractor,
    chunkTokenizer
  ))

val data = Seq(
  "Hello world, my name is Michael, I am an artist and I work at Benezar",
  "Robert, an engineer from Farendell, graduated last year. The other one, Lucas, graduated last week."
).toDF("text")
val result = pipeline.fit(data).transform(data)

result.selectExpr("entity.result as entity" , "chunk_token.result as chunk_token").show(false)
+-----------------------------------------------+---------------------------------------------------+
|entity                                         |chunk_token                                        |
+-----------------------------------------------+---------------------------------------------------+
|[world, Michael, work at Benezar]              |[world, Michael, work, at, Benezar]                |
|[engineer from Farendell, last year, last week]|[engineer, from, Farendell, last, year, last, week]|
+-----------------------------------------------+---------------------------------------------------+

Linear Supertypes

Tokenizer, AnnotatorApproach[TokenizerModel], CanBeLazy, DefaultParamsWritable, MLWritable, HasOutputAnnotatorType, HasOutputAnnotationCol, HasInputAnnotationCols, Estimator[TokenizerModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any

Ordering

Grouped
Alphabetic
By Inheritance

Inherited

ChunkTokenizer
Tokenizer
AnnotatorApproach
CanBeLazy
DefaultParamsWritable
MLWritable
HasOutputAnnotatorType
HasOutputAnnotationCol
HasInputAnnotationCols
Estimator
PipelineStage
Logging
Params
Serializable
Serializable
Identifiable
AnyRef
Any

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Visibility

Public
All

Instance Constructors

new ChunkTokenizer()
new ChunkTokenizer(uid: String)
uid
required internal uid for saving annotator

Type Members

type AnnotatorType = String

Definition Classes
HasOutputAnnotatorType

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T

Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): TokenizerModel

Attributes
protected
Definition Classes
AnnotatorApproach
def addContextChars(v: String): ChunkTokenizer.this.type
Add one character string to rip off from tokens, such as parenthesis or question marks.
Add one character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
def addException(value: String): ChunkTokenizer.this.type
Add a single exception
Add a single exception

Definition Classes
Tokenizer
def addInfixPattern(value: String): ChunkTokenizer.this.type
Add an extension pattern regex with groups to the top of thsetExceptionse rules (will target first, from more specific to the more general).
Add an extension pattern regex with groups to the top of thsetExceptionse rules (will target first, from more specific to the more general).

Definition Classes
Tokenizer
def addSplitChars(v: String): ChunkTokenizer.this.type
One character string to split tokens inside, such as hyphens.
One character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
final def asInstanceOf[T0]: T0

Definition Classes
Any
def beforeTraining(spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
def buildRuleFactory: RuleFactory
Build rule factory which combines all defined parameters to build regex that is applied to tokens
Build rule factory which combines all defined parameters to build regex that is applied to tokens

Definition Classes
Tokenizer
val caseSensitiveExceptions: BooleanParam
Whether to care for case sensitiveness in exceptions (Default: true)
Whether to care for case sensitiveness in exceptions (Default: true)

Definition Classes
Tokenizer
final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def clear(param: Param[_]): ChunkTokenizer.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
val contextChars: StringArrayParam
Character list used to separate from token boundaries (Default: Array(".", ",", ";", ":", "!", "?", "*", "-", "(", ")", "\"", "'"))
Character list used to separate from token boundaries (Default: Array(".", ",", ";", ":", "!", "?", "*", "-", "(", ")", "\"", "'"))

Definition Classes
Tokenizer
final def copy(extra: ParamMap): Estimator[TokenizerModel]

Definition Classes
AnnotatorApproach → Estimator → PipelineStage → Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
val description: String
Annotator that identifies points of analysis in a useful manner
Annotator that identifies points of analysis in a useful manner

Definition Classes
Tokenizer → AnnotatorApproach
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
val exceptions: StringArrayParam
Words that won't be affected by tokenization rules
Words that won't be affected by tokenization rules

Definition Classes
Tokenizer
val exceptionsPath: ExternalResourceParam
Path to file containing list of exceptions
Path to file containing list of exceptions

Definition Classes
Tokenizer
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
def finalize(): Unit

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def fit(dataset: Dataset[_]): TokenizerModel

Definition Classes
AnnotatorApproach → Estimator
def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[TokenizerModel]

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], paramMap: ParamMap): TokenizerModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TokenizerModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()
final def get[T](param: Param[T]): Option[T]

Definition Classes
Params
def getCaseSensitiveExceptions(value: Boolean): Boolean
Whether to follow case sensitiveness for matching exceptions in text
Whether to follow case sensitiveness for matching exceptions in text

Definition Classes
Tokenizer
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@native()
def getContextChars: Array[String]
List of 1 character string to rip off from tokens, such as parenthesis or question marks.
List of 1 character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
def getExceptions: Array[String]

Definition Classes
Tokenizer
def getInfixPatterns: Array[String]
Add an extension pattern regex with groups to the top of the rules (will target first, from more specific to the more general).
Add an extension pattern regex with groups to the top of the rules (will target first, from more specific to the more general).

Definition Classes
Tokenizer
def getInputCols: Array[String]
returns
input annotations columns currently used

Definition Classes
HasInputAnnotationCols
def getLazyAnnotator: Boolean

Definition Classes
CanBeLazy
def getMaxLength(value: Int): Int
Get the maximum allowed length for each token
Get the maximum allowed length for each token

Definition Classes
Tokenizer
def getMinLength(value: Int): Int
Get the minimum allowed length for each token
Get the minimum allowed length for each token

Definition Classes
Tokenizer
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
final def getOutputCol: String
Gets annotation column name going to generate
Gets annotation column name going to generate

Definition Classes
HasOutputAnnotationCol
def getParam(paramName: String): Param[Any]

Definition Classes
Params
def getPrefixPattern: String
Regex to identify subtokens that come in the beginning of the token.
Regex to identify subtokens that come in the beginning of the token. Regex has to start with \\A and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def getSplitChars: Array[String]
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def getSplitPattern: String
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def getSuffixPattern: String
Regex to identify subtokens that are in the end of the token.
Regex to identify subtokens that are in the end of the token. Regex has to end with \\z and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def getTargetPattern: String
Basic regex rule to identify a candidate for tokenization.
Basic regex rule to identify a candidate for tokenization. Defaults to \\S+ which means anything not a space

Definition Classes
Tokenizer
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
def hashCode(): Int

Definition Classes
AnyRef → Any
Annotations
@native()

val infixPatterns: StringArrayParam

Regex patterns that match tokens within a single target.

Regex patterns that match tokens within a single target. groups identify different sub-tokens. multiple defaults

Infix patterns must use regex group. Notice each group will result in separate token

Example:

import org.apache.spark.ml.Pipeline
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("l'une d'un l'un, des l'extrême des l'extreme")).toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")
val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setInfixPatterns(Array("([\\p{L}\\w]+'{1})([\\p{L}\\w]+)"))
new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: l', une, d', un, l', un, , , des, l', extrême, des, l', extreme

Definition Classes: Tokenizer

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
val inputAnnotatorTypes: Array[AnnotatorType]
Input Annotator Type : CHUNK
Input Annotator Type : CHUNK

Definition Classes
ChunkTokenizer → Tokenizer → HasInputAnnotationCols
final val inputCols: StringArrayParam
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def isDefined(param: Param[_]): Boolean

Definition Classes
Params
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def isSet(param: Param[_]): Boolean

Definition Classes
Params
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
val lazyAnnotator: BooleanParam

Definition Classes
CanBeLazy
def log: Logger

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logName: String

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
val maxLength: IntParam
Set the maximum allowed length for each token
Set the maximum allowed length for each token

Definition Classes
Tokenizer
val minLength: IntParam
Set the minimum allowed length for each token
Set the minimum allowed length for each token

Definition Classes
Tokenizer
def msgHelper(schema: StructType): String

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@native()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@native()
def onTrained(model: TokenizerModel, spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
val optionalInputAnnotatorTypes: Array[String]

Definition Classes
HasInputAnnotationCols
val outputAnnotatorType: AnnotatorType
Output Annotator Type : TOKEN
Output Annotator Type : TOKEN

Definition Classes
ChunkTokenizer → Tokenizer → HasOutputAnnotatorType
final val outputCol: Param[String]

Attributes
protected
Definition Classes
HasOutputAnnotationCol
lazy val params: Array[Param[_]]

Definition Classes
Params
val prefixPattern: Param[String]
Regex with groups and begins with \\A to match target prefix.
Regex with groups and begins with \\A to match target prefix. Overrides contextCharacters Param

Definition Classes
Tokenizer
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
final def set(paramPair: ParamPair[_]): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): ChunkTokenizer.this.type

Definition Classes
Params
def setCaseSensitiveExceptions(value: Boolean): ChunkTokenizer.this.type
Whether to follow case sensitiveness for matching exceptions in text
Whether to follow case sensitiveness for matching exceptions in text

Definition Classes
Tokenizer
def setContextChars(v: Array[String]): ChunkTokenizer.this.type
List of 1 character string to rip off from tokens, such as parenthesis or question marks.
List of 1 character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
final def setDefault(paramPairs: ParamPair[_]*): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): ChunkTokenizer.this.type

Attributes
protected[org.apache.spark.ml]
Definition Classes
Params
def setExceptions(value: Array[String]): ChunkTokenizer.this.type
List of tokens to not alter at all.
List of tokens to not alter at all. Allows composite tokens like two worded tokens that the user may not want to split.

Definition Classes
Tokenizer
def setExceptionsPath(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("format" -> "text")): ChunkTokenizer.this.type
Path to txt file with list of token exceptions
Path to txt file with list of token exceptions

Definition Classes
Tokenizer
def setInfixPatterns(value: Array[String]): ChunkTokenizer.this.type
Set a list of Regex patterns that match tokens within a single target.
Set a list of Regex patterns that match tokens within a single target. Groups identify different sub-tokens. multiple defaults

Definition Classes
Tokenizer
final def setInputCols(value: String*): ChunkTokenizer.this.type

Definition Classes
HasInputAnnotationCols
def setInputCols(value: Array[String]): ChunkTokenizer.this.type
Overrides required annotators column if different than default
Overrides required annotators column if different than default

Definition Classes
HasInputAnnotationCols
def setLazyAnnotator(value: Boolean): ChunkTokenizer.this.type

Definition Classes
CanBeLazy
def setMaxLength(value: Int): ChunkTokenizer.this.type
Get the maximum allowed length for each token
Get the maximum allowed length for each token

Definition Classes
Tokenizer
def setMinLength(value: Int): ChunkTokenizer.this.type
Set the minimum allowed length for each token
Set the minimum allowed length for each token

Definition Classes
Tokenizer
final def setOutputCol(value: String): ChunkTokenizer.this.type
Overrides annotation column name when transforming
Overrides annotation column name when transforming

Definition Classes
HasOutputAnnotationCol
def setPrefixPattern(value: String): ChunkTokenizer.this.type
Regex to identify subtokens that come in the beginning of the token.
Regex to identify subtokens that come in the beginning of the token. Regex has to start with \\A and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def setSplitChars(v: Array[String]): ChunkTokenizer.this.type
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def setSplitPattern(value: String): ChunkTokenizer.this.type
Regex pattern to separate from the inside of tokens.
Regex pattern to separate from the inside of tokens. Takes priority over splitChars.

Definition Classes
Tokenizer
def setSuffixPattern(value: String): ChunkTokenizer.this.type
Regex to identify subtokens that are in the end of the token.
Regex to identify subtokens that are in the end of the token. Regex has to end with \\z and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def setTargetPattern(value: String): ChunkTokenizer.this.type
Set a basic regex rule to identify token candidates in text.
Set a basic regex rule to identify token candidates in text.

Definition Classes
Tokenizer
val splitChars: StringArrayParam
Character list used to separate from the inside of tokens
Character list used to separate from the inside of tokens

Definition Classes
Tokenizer

val splitPattern: Param[String]

Pattern to separate from the inside of tokens.

Pattern to separate from the inside of tokens. takes priority over splitChars.

This pattern will be applied to the tokens which where extracted with the target pattern previously

Example:

import org.apache.spark.ml.Pipeline

import com.johnsnowlabs.nlp.annotators.Tokenizer

import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("Tokens in this-text will#be#split on hashtags-and#dashes")).toDF("text")

val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")

val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setSplitPattern("-|#")

new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: Tokens, in, this, text, will, be, split, on, hashtags, and, dashes

Definition Classes: Tokenizer

val suffixPattern: Param[String]
Regex with groups and ends with \\z to match target suffix.
Regex with groups and ends with \\z to match target suffix. Overrides contextCharacters Param

Definition Classes
Tokenizer
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef

val targetPattern: Param[String]

Pattern to grab from text as token candidates.

Pattern to grab from text as token candidates. (Default: "\\S+")

Defaults to: "\\S+" which means anything not a space will be matched and considered as a token candidate, This will cause text to be split on on white spaces to yield token candidates.

This rule will be added to the BREAK_PATTERN varaible, which is used to yield token candidates.

import org.apache.spark.ml.Pipeline
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("I only consider lowercase characters and NOT UPPERCASED and only the numbers 0,1, to 7 as tokens but not 8 or 9")).toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")
val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setTargetPattern("a-z-0-7")
new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: only, consider, lowercase, characters, and, and, only, the, numbers, 0, 1, to, 7, as, tokens, but, not, or

Definition Classes: Tokenizer

def toString(): String

Definition Classes
Identifiable → AnyRef → Any
def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): TokenizerModel
Clears out rules and constructs a new rule for every combination of rules provided .
Clears out rules and constructs a new rule for every combination of rules provided . The strategy is to catch one token per regex group. User may add its own groups if needs targets to be tokenized separately from the rest

Definition Classes
ChunkTokenizer → Tokenizer → AnnotatorApproach
final def transformSchema(schema: StructType): StructType
requirement for pipeline transformation validation.
requirement for pipeline transformation validation. It is called on fit()

Definition Classes
AnnotatorApproach → PipelineStage
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String

Definition Classes
ChunkTokenizer → Tokenizer → Identifiable
def validate(schema: StructType): Boolean
takes a Dataset and checks to see if all the required annotation types are present.
takes a Dataset and checks to see if all the required annotation types are present.
schema
to be validated
returns
True if all the required types are present, else false

Attributes
protected
Definition Classes
AnnotatorApproach
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
def write: MLWriter

Definition Classes
DefaultParamsWritable → MLWritable

Inherited from Tokenizer

Value Members

def addContextChars(v: String): ChunkTokenizer.this.type
Add one character string to rip off from tokens, such as parenthesis or question marks.
Add one character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
def addException(value: String): ChunkTokenizer.this.type
Add a single exception
Add a single exception

Definition Classes
Tokenizer
def addInfixPattern(value: String): ChunkTokenizer.this.type
Add an extension pattern regex with groups to the top of thsetExceptionse rules (will target first, from more specific to the more general).
Add an extension pattern regex with groups to the top of thsetExceptionse rules (will target first, from more specific to the more general).

Definition Classes
Tokenizer
def addSplitChars(v: String): ChunkTokenizer.this.type
One character string to split tokens inside, such as hyphens.
One character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def buildRuleFactory: RuleFactory
Build rule factory which combines all defined parameters to build regex that is applied to tokens
Build rule factory which combines all defined parameters to build regex that is applied to tokens

Definition Classes
Tokenizer
val caseSensitiveExceptions: BooleanParam
Whether to care for case sensitiveness in exceptions (Default: true)
Whether to care for case sensitiveness in exceptions (Default: true)

Definition Classes
Tokenizer
val contextChars: StringArrayParam
Character list used to separate from token boundaries (Default: Array(".", ",", ";", ":", "!", "?", "*", "-", "(", ")", "\"", "'"))
Character list used to separate from token boundaries (Default: Array(".", ",", ";", ":", "!", "?", "*", "-", "(", ")", "\"", "'"))

Definition Classes
Tokenizer
val description: String
Annotator that identifies points of analysis in a useful manner
Annotator that identifies points of analysis in a useful manner

Definition Classes
Tokenizer → AnnotatorApproach
val exceptions: StringArrayParam
Words that won't be affected by tokenization rules
Words that won't be affected by tokenization rules

Definition Classes
Tokenizer
val exceptionsPath: ExternalResourceParam
Path to file containing list of exceptions
Path to file containing list of exceptions

Definition Classes
Tokenizer
def getCaseSensitiveExceptions(value: Boolean): Boolean
Whether to follow case sensitiveness for matching exceptions in text
Whether to follow case sensitiveness for matching exceptions in text

Definition Classes
Tokenizer
def getContextChars: Array[String]
List of 1 character string to rip off from tokens, such as parenthesis or question marks.
List of 1 character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
def getExceptions: Array[String]

Definition Classes
Tokenizer
def getInfixPatterns: Array[String]
Add an extension pattern regex with groups to the top of the rules (will target first, from more specific to the more general).
Add an extension pattern regex with groups to the top of the rules (will target first, from more specific to the more general).

Definition Classes
Tokenizer
def getMaxLength(value: Int): Int
Get the maximum allowed length for each token
Get the maximum allowed length for each token

Definition Classes
Tokenizer
def getMinLength(value: Int): Int
Get the minimum allowed length for each token
Get the minimum allowed length for each token

Definition Classes
Tokenizer
def getPrefixPattern: String
Regex to identify subtokens that come in the beginning of the token.
Regex to identify subtokens that come in the beginning of the token. Regex has to start with \\A and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def getSplitChars: Array[String]
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def getSplitPattern: String
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def getSuffixPattern: String
Regex to identify subtokens that are in the end of the token.
Regex to identify subtokens that are in the end of the token. Regex has to end with \\z and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def getTargetPattern: String
Basic regex rule to identify a candidate for tokenization.
Basic regex rule to identify a candidate for tokenization. Defaults to \\S+ which means anything not a space

Definition Classes
Tokenizer

val infixPatterns: StringArrayParam

Regex patterns that match tokens within a single target.

Regex patterns that match tokens within a single target. groups identify different sub-tokens. multiple defaults

Infix patterns must use regex group. Notice each group will result in separate token

Example:

import org.apache.spark.ml.Pipeline
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("l'une d'un l'un, des l'extrême des l'extreme")).toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")
val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setInfixPatterns(Array("([\\p{L}\\w]+'{1})([\\p{L}\\w]+)"))
new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: l', une, d', un, l', un, , , des, l', extrême, des, l', extreme

Definition Classes: Tokenizer

val maxLength: IntParam
Set the maximum allowed length for each token
Set the maximum allowed length for each token

Definition Classes
Tokenizer
val minLength: IntParam
Set the minimum allowed length for each token
Set the minimum allowed length for each token

Definition Classes
Tokenizer
val prefixPattern: Param[String]
Regex with groups and begins with \\A to match target prefix.
Regex with groups and begins with \\A to match target prefix. Overrides contextCharacters Param

Definition Classes
Tokenizer
def setCaseSensitiveExceptions(value: Boolean): ChunkTokenizer.this.type
Whether to follow case sensitiveness for matching exceptions in text
Whether to follow case sensitiveness for matching exceptions in text

Definition Classes
Tokenizer
def setContextChars(v: Array[String]): ChunkTokenizer.this.type
List of 1 character string to rip off from tokens, such as parenthesis or question marks.
List of 1 character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
def setExceptions(value: Array[String]): ChunkTokenizer.this.type
List of tokens to not alter at all.
List of tokens to not alter at all. Allows composite tokens like two worded tokens that the user may not want to split.

Definition Classes
Tokenizer
def setExceptionsPath(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("format" -> "text")): ChunkTokenizer.this.type
Path to txt file with list of token exceptions
Path to txt file with list of token exceptions

Definition Classes
Tokenizer
def setInfixPatterns(value: Array[String]): ChunkTokenizer.this.type
Set a list of Regex patterns that match tokens within a single target.
Set a list of Regex patterns that match tokens within a single target. Groups identify different sub-tokens. multiple defaults

Definition Classes
Tokenizer
def setMaxLength(value: Int): ChunkTokenizer.this.type
Get the maximum allowed length for each token
Get the maximum allowed length for each token

Definition Classes
Tokenizer
def setMinLength(value: Int): ChunkTokenizer.this.type
Set the minimum allowed length for each token
Set the minimum allowed length for each token

Definition Classes
Tokenizer
def setPrefixPattern(value: String): ChunkTokenizer.this.type
Regex to identify subtokens that come in the beginning of the token.
Regex to identify subtokens that come in the beginning of the token. Regex has to start with \\A and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def setSplitChars(v: Array[String]): ChunkTokenizer.this.type
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def setSplitPattern(value: String): ChunkTokenizer.this.type
Regex pattern to separate from the inside of tokens.
Regex pattern to separate from the inside of tokens. Takes priority over splitChars.

Definition Classes
Tokenizer
def setSuffixPattern(value: String): ChunkTokenizer.this.type
Regex to identify subtokens that are in the end of the token.
Regex to identify subtokens that are in the end of the token. Regex has to end with \\z and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def setTargetPattern(value: String): ChunkTokenizer.this.type
Set a basic regex rule to identify token candidates in text.
Set a basic regex rule to identify token candidates in text.

Definition Classes
Tokenizer
val splitChars: StringArrayParam
Character list used to separate from the inside of tokens
Character list used to separate from the inside of tokens

Definition Classes
Tokenizer

val splitPattern: Param[String]

Pattern to separate from the inside of tokens.

Pattern to separate from the inside of tokens. takes priority over splitChars.

This pattern will be applied to the tokens which where extracted with the target pattern previously

Example:

import org.apache.spark.ml.Pipeline

import com.johnsnowlabs.nlp.annotators.Tokenizer

import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("Tokens in this-text will#be#split on hashtags-and#dashes")).toDF("text")

val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")

val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setSplitPattern("-|#")

new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: Tokens, in, this, text, will, be, split, on, hashtags, and, dashes

Definition Classes: Tokenizer

val suffixPattern: Param[String]
Regex with groups and ends with \\z to match target suffix.
Regex with groups and ends with \\z to match target suffix. Overrides contextCharacters Param

Definition Classes
Tokenizer

val targetPattern: Param[String]

Pattern to grab from text as token candidates.

Pattern to grab from text as token candidates. (Default: "\\S+")

Defaults to: "\\S+" which means anything not a space will be matched and considered as a token candidate, This will cause text to be split on on white spaces to yield token candidates.

This rule will be added to the BREAK_PATTERN varaible, which is used to yield token candidates.

import org.apache.spark.ml.Pipeline
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("I only consider lowercase characters and NOT UPPERCASED and only the numbers 0,1, to 7 as tokens but not 8 or 9")).toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")
val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setTargetPattern("a-z-0-7")
new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: only, consider, lowercase, characters, and, and, only, the, numbers, 0, 1, to, 7, as, tokens, but, not, or

Definition Classes: Tokenizer

Inherited from AnnotatorApproach[TokenizerModel]

Value Members

def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): TokenizerModel

Attributes
protected
Definition Classes
AnnotatorApproach
def beforeTraining(spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
final def copy(extra: ParamMap): Estimator[TokenizerModel]

Definition Classes
AnnotatorApproach → Estimator → PipelineStage → Params
final def fit(dataset: Dataset[_]): TokenizerModel

Definition Classes
AnnotatorApproach → Estimator
def onTrained(model: TokenizerModel, spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
final def transformSchema(schema: StructType): StructType
requirement for pipeline transformation validation.
requirement for pipeline transformation validation. It is called on fit()

Definition Classes
AnnotatorApproach → PipelineStage
def validate(schema: StructType): Boolean
takes a Dataset and checks to see if all the required annotation types are present.
takes a Dataset and checks to see if all the required annotation types are present.
schema
to be validated
returns
True if all the required types are present, else false

Attributes
protected
Definition Classes
AnnotatorApproach

Inherited from CanBeLazy

Value Members

def getLazyAnnotator: Boolean

Definition Classes
CanBeLazy
val lazyAnnotator: BooleanParam

Definition Classes
CanBeLazy
def setLazyAnnotator(value: Boolean): ChunkTokenizer.this.type

Definition Classes
CanBeLazy

Inherited from DefaultParamsWritable

Value Members

def write: MLWriter

Definition Classes
DefaultParamsWritable → MLWritable

Inherited from MLWritable

Value Members

def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )

Inherited from HasOutputAnnotationCol

Value Members

final def getOutputCol: String
Gets annotation column name going to generate
Gets annotation column name going to generate

Definition Classes
HasOutputAnnotationCol
final val outputCol: Param[String]

Attributes
protected
Definition Classes
HasOutputAnnotationCol
final def setOutputCol(value: String): ChunkTokenizer.this.type
Overrides annotation column name when transforming
Overrides annotation column name when transforming

Definition Classes
HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Value Members

final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

Attributes
protected
Definition Classes
HasInputAnnotationCols
def getInputCols: Array[String]
returns
input annotations columns currently used

Definition Classes
HasInputAnnotationCols
final val inputCols: StringArrayParam
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

Attributes
protected
Definition Classes
HasInputAnnotationCols
def msgHelper(schema: StructType): String

Attributes
protected
Definition Classes
HasInputAnnotationCols
val optionalInputAnnotatorTypes: Array[String]

Definition Classes
HasInputAnnotationCols
final def setInputCols(value: String*): ChunkTokenizer.this.type

Definition Classes
HasInputAnnotationCols
def setInputCols(value: Array[String]): ChunkTokenizer.this.type
Overrides required annotators column if different than default
Overrides required annotators column if different than default

Definition Classes
HasInputAnnotationCols

Inherited from Estimator[TokenizerModel]

Value Members

def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[TokenizerModel]

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], paramMap: ParamMap): TokenizerModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TokenizerModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()

Inherited from PipelineStage

Value Members

def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()

Inherited from Logging

Value Members

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
def log: Logger

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logName: String

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging

Inherited from Params

Value Members

final def $[T](param: Param[T]): T

Attributes
protected
Definition Classes
Params
final def clear(param: Param[_]): ChunkTokenizer.this.type

Definition Classes
Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
final def get[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
def getParam(paramName: String): Param[Any]

Definition Classes
Params
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
final def isDefined(param: Param[_]): Boolean

Definition Classes
Params
final def isSet(param: Param[_]): Boolean

Definition Classes
Params
lazy val params: Array[Param[_]]

Definition Classes
Params
final def set(paramPair: ParamPair[_]): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): ChunkTokenizer.this.type

Definition Classes
Params
final def setDefault(paramPairs: ParamPair[_]*): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): ChunkTokenizer.this.type

Attributes
protected[org.apache.spark.ml]
Definition Classes
Params

Inherited from Identifiable

Value Members

def toString(): String

Definition Classes
Identifiable → AnyRef → Any

Inherited from AnyRef

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def clone(): AnyRef

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@native()
def hashCode(): Int

Definition Classes
AnyRef → Any
Annotations
@native()
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@native()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@native()
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... ) @native()

Inherited from Any

Value Members

final def asInstanceOf[T0]: T0

Definition Classes
Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any

Parameters

A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.

val caseSensitiveExceptions: BooleanParam
Whether to care for case sensitiveness in exceptions (Default: true)
Whether to care for case sensitiveness in exceptions (Default: true)

Definition Classes
Tokenizer
val contextChars: StringArrayParam
Character list used to separate from token boundaries (Default: Array(".", ",", ";", ":", "!", "?", "*", "-", "(", ")", "\"", "'"))
Character list used to separate from token boundaries (Default: Array(".", ",", ";", ":", "!", "?", "*", "-", "(", ")", "\"", "'"))

Definition Classes
Tokenizer
val exceptions: StringArrayParam
Words that won't be affected by tokenization rules
Words that won't be affected by tokenization rules

Definition Classes
Tokenizer
val exceptionsPath: ExternalResourceParam
Path to file containing list of exceptions
Path to file containing list of exceptions

Definition Classes
Tokenizer

val infixPatterns: StringArrayParam

Regex patterns that match tokens within a single target.

Regex patterns that match tokens within a single target. groups identify different sub-tokens. multiple defaults

Infix patterns must use regex group. Notice each group will result in separate token

Example:

import org.apache.spark.ml.Pipeline
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("l'une d'un l'un, des l'extrême des l'extreme")).toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")
val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setInfixPatterns(Array("([\\p{L}\\w]+'{1})([\\p{L}\\w]+)"))
new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: l', une, d', un, l', un, , , des, l', extrême, des, l', extreme

Definition Classes: Tokenizer

val maxLength: IntParam
Set the maximum allowed length for each token
Set the maximum allowed length for each token

Definition Classes
Tokenizer
val minLength: IntParam
Set the minimum allowed length for each token
Set the minimum allowed length for each token

Definition Classes
Tokenizer
val prefixPattern: Param[String]
Regex with groups and begins with \\A to match target prefix.
Regex with groups and begins with \\A to match target prefix. Overrides contextCharacters Param

Definition Classes
Tokenizer
val splitChars: StringArrayParam
Character list used to separate from the inside of tokens
Character list used to separate from the inside of tokens

Definition Classes
Tokenizer

val splitPattern: Param[String]

Pattern to separate from the inside of tokens.

Pattern to separate from the inside of tokens. takes priority over splitChars.

This pattern will be applied to the tokens which where extracted with the target pattern previously

Example:

import org.apache.spark.ml.Pipeline

import com.johnsnowlabs.nlp.annotators.Tokenizer

import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("Tokens in this-text will#be#split on hashtags-and#dashes")).toDF("text")

val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")

val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setSplitPattern("-|#")

new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: Tokens, in, this, text, will, be, split, on, hashtags, and, dashes

Definition Classes: Tokenizer

val suffixPattern: Param[String]
Regex with groups and ends with \\z to match target suffix.
Regex with groups and ends with \\z to match target suffix. Overrides contextCharacters Param

Definition Classes
Tokenizer

val targetPattern: Param[String]

Pattern to grab from text as token candidates.

Pattern to grab from text as token candidates. (Default: "\\S+")

Defaults to: "\\S+" which means anything not a space will be matched and considered as a token candidate, This will cause text to be split on on white spaces to yield token candidates.

This rule will be added to the BREAK_PATTERN varaible, which is used to yield token candidates.

import org.apache.spark.ml.Pipeline
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.DocumentAssembler

val textDf = sqlContext.sparkContext.parallelize(Array("I only consider lowercase characters and NOT UPPERCASED and only the numbers 0,1, to 7 as tokens but not 8 or 9")).toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("sentences")
val tokenizer = new Tokenizer().setInputCols("sentences").setOutputCol("tokens").setTargetPattern("a-z-0-7")
new Pipeline().setStages(Array(documentAssembler, tokenizer)).fit(textDf).transform(textDf).select("tokens.result").show(false)

This will yield: only, consider, lowercase, characters, and, and, only, the, numbers, 0, 1, to, 7, as, tokens, but, not, or

Definition Classes: Tokenizer

Annotator types

Required input and expected output annotator types

val inputAnnotatorTypes: Array[AnnotatorType]
Input Annotator Type : CHUNK
Input Annotator Type : CHUNK

Definition Classes
ChunkTokenizer → Tokenizer → HasInputAnnotationCols
val outputAnnotatorType: AnnotatorType
Output Annotator Type : TOKEN
Output Annotator Type : TOKEN

Definition Classes
ChunkTokenizer → Tokenizer → HasOutputAnnotatorType

Members

type AnnotatorType = String

Definition Classes
HasOutputAnnotatorType

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T

Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): TokenizerModel

Attributes
protected
Definition Classes
AnnotatorApproach
final def asInstanceOf[T0]: T0

Definition Classes
Any
def beforeTraining(spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
def buildRuleFactory: RuleFactory
Build rule factory which combines all defined parameters to build regex that is applied to tokens
Build rule factory which combines all defined parameters to build regex that is applied to tokens

Definition Classes
Tokenizer
final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def clear(param: Param[_]): ChunkTokenizer.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
final def copy(extra: ParamMap): Estimator[TokenizerModel]

Definition Classes
AnnotatorApproach → Estimator → PipelineStage → Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
val description: String
Annotator that identifies points of analysis in a useful manner
Annotator that identifies points of analysis in a useful manner

Definition Classes
Tokenizer → AnnotatorApproach
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
def finalize(): Unit

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def fit(dataset: Dataset[_]): TokenizerModel

Definition Classes
AnnotatorApproach → Estimator
def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[TokenizerModel]

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], paramMap: ParamMap): TokenizerModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TokenizerModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()
final def get[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@native()
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
def getInputCols: Array[String]
returns
input annotations columns currently used

Definition Classes
HasInputAnnotationCols
def getLazyAnnotator: Boolean

Definition Classes
CanBeLazy
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
final def getOutputCol: String
Gets annotation column name going to generate
Gets annotation column name going to generate

Definition Classes
HasOutputAnnotationCol
def getParam(paramName: String): Param[Any]

Definition Classes
Params
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
def hashCode(): Int

Definition Classes
AnyRef → Any
Annotations
@native()
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
final val inputCols: StringArrayParam
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def isDefined(param: Param[_]): Boolean

Definition Classes
Params
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def isSet(param: Param[_]): Boolean

Definition Classes
Params
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
val lazyAnnotator: BooleanParam

Definition Classes
CanBeLazy
def log: Logger

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logName: String

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def msgHelper(schema: StructType): String

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@native()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@native()
def onTrained(model: TokenizerModel, spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
val optionalInputAnnotatorTypes: Array[String]

Definition Classes
HasInputAnnotationCols
final val outputCol: Param[String]

Attributes
protected
Definition Classes
HasOutputAnnotationCol
lazy val params: Array[Param[_]]

Definition Classes
Params
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
final def set(paramPair: ParamPair[_]): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): ChunkTokenizer.this.type

Definition Classes
Params
final def setDefault(paramPairs: ParamPair[_]*): ChunkTokenizer.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): ChunkTokenizer.this.type

Attributes
protected[org.apache.spark.ml]
Definition Classes
Params
final def setInputCols(value: String*): ChunkTokenizer.this.type

Definition Classes
HasInputAnnotationCols
def setInputCols(value: Array[String]): ChunkTokenizer.this.type
Overrides required annotators column if different than default
Overrides required annotators column if different than default

Definition Classes
HasInputAnnotationCols
def setLazyAnnotator(value: Boolean): ChunkTokenizer.this.type

Definition Classes
CanBeLazy
final def setOutputCol(value: String): ChunkTokenizer.this.type
Overrides annotation column name when transforming
Overrides annotation column name when transforming

Definition Classes
HasOutputAnnotationCol
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): TokenizerModel
Clears out rules and constructs a new rule for every combination of rules provided .
Clears out rules and constructs a new rule for every combination of rules provided . The strategy is to catch one token per regex group. User may add its own groups if needs targets to be tokenized separately from the rest

Definition Classes
ChunkTokenizer → Tokenizer → AnnotatorApproach
final def transformSchema(schema: StructType): StructType
requirement for pipeline transformation validation.
requirement for pipeline transformation validation. It is called on fit()

Definition Classes
AnnotatorApproach → PipelineStage
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String

Definition Classes
ChunkTokenizer → Tokenizer → Identifiable
def validate(schema: StructType): Boolean
takes a Dataset and checks to see if all the required annotation types are present.
takes a Dataset and checks to see if all the required annotation types are present.
schema
to be validated
returns
True if all the required types are present, else false

Attributes
protected
Definition Classes
AnnotatorApproach
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
def write: MLWriter

Definition Classes
DefaultParamsWritable → MLWritable

Parameter setters

def addContextChars(v: String): ChunkTokenizer.this.type
Add one character string to rip off from tokens, such as parenthesis or question marks.
Add one character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
def addException(value: String): ChunkTokenizer.this.type
Add a single exception
Add a single exception

Definition Classes
Tokenizer
def addInfixPattern(value: String): ChunkTokenizer.this.type
Add an extension pattern regex with groups to the top of thsetExceptionse rules (will target first, from more specific to the more general).
Add an extension pattern regex with groups to the top of thsetExceptionse rules (will target first, from more specific to the more general).

Definition Classes
Tokenizer
def addSplitChars(v: String): ChunkTokenizer.this.type
One character string to split tokens inside, such as hyphens.
One character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def getExceptions: Array[String]

Definition Classes
Tokenizer
def setContextChars(v: Array[String]): ChunkTokenizer.this.type
List of 1 character string to rip off from tokens, such as parenthesis or question marks.
List of 1 character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
def setExceptions(value: Array[String]): ChunkTokenizer.this.type
List of tokens to not alter at all.
List of tokens to not alter at all. Allows composite tokens like two worded tokens that the user may not want to split.

Definition Classes
Tokenizer
def setInfixPatterns(value: Array[String]): ChunkTokenizer.this.type
Set a list of Regex patterns that match tokens within a single target.
Set a list of Regex patterns that match tokens within a single target. Groups identify different sub-tokens. multiple defaults

Definition Classes
Tokenizer
def setMaxLength(value: Int): ChunkTokenizer.this.type
Get the maximum allowed length for each token
Get the maximum allowed length for each token

Definition Classes
Tokenizer
def setMinLength(value: Int): ChunkTokenizer.this.type
Set the minimum allowed length for each token
Set the minimum allowed length for each token

Definition Classes
Tokenizer
def setPrefixPattern(value: String): ChunkTokenizer.this.type
Regex to identify subtokens that come in the beginning of the token.
Regex to identify subtokens that come in the beginning of the token. Regex has to start with \\A and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def setSplitChars(v: Array[String]): ChunkTokenizer.this.type
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def setSplitPattern(value: String): ChunkTokenizer.this.type
Regex pattern to separate from the inside of tokens.
Regex pattern to separate from the inside of tokens. Takes priority over splitChars.

Definition Classes
Tokenizer
def setSuffixPattern(value: String): ChunkTokenizer.this.type
Regex to identify subtokens that are in the end of the token.
Regex to identify subtokens that are in the end of the token. Regex has to end with \\z and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def setTargetPattern(value: String): ChunkTokenizer.this.type
Set a basic regex rule to identify token candidates in text.
Set a basic regex rule to identify token candidates in text.

Definition Classes
Tokenizer

Parameter getters

def getCaseSensitiveExceptions(value: Boolean): Boolean
Whether to follow case sensitiveness for matching exceptions in text
Whether to follow case sensitiveness for matching exceptions in text

Definition Classes
Tokenizer
def getContextChars: Array[String]
List of 1 character string to rip off from tokens, such as parenthesis or question marks.
List of 1 character string to rip off from tokens, such as parenthesis or question marks. Ignored if using prefix, infix or suffix patterns.

Definition Classes
Tokenizer
def getInfixPatterns: Array[String]
Add an extension pattern regex with groups to the top of the rules (will target first, from more specific to the more general).
Add an extension pattern regex with groups to the top of the rules (will target first, from more specific to the more general).

Definition Classes
Tokenizer
def getMaxLength(value: Int): Int
Get the maximum allowed length for each token
Get the maximum allowed length for each token

Definition Classes
Tokenizer
def getMinLength(value: Int): Int
Get the minimum allowed length for each token
Get the minimum allowed length for each token

Definition Classes
Tokenizer
def getPrefixPattern: String
Regex to identify subtokens that come in the beginning of the token.
Regex to identify subtokens that come in the beginning of the token. Regex has to start with \\A and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def getSplitChars: Array[String]
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def getSplitPattern: String
List of 1 character string to split tokens inside, such as hyphens.
List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

Definition Classes
Tokenizer
def getSuffixPattern: String
Regex to identify subtokens that are in the end of the token.
Regex to identify subtokens that are in the end of the token. Regex has to end with \\z and must contain groups (). Each group will become a separate token within the prefix. Defaults to non-letter characters. e.g. quotes or parenthesis

Definition Classes
Tokenizer
def getTargetPattern: String
Basic regex rule to identify a candidate for tokenization.
Basic regex rule to identify a candidate for tokenization. Defaults to \\S+ which means anything not a space

Definition Classes
Tokenizer
def setCaseSensitiveExceptions(value: Boolean): ChunkTokenizer.this.type
Whether to follow case sensitiveness for matching exceptions in text
Whether to follow case sensitiveness for matching exceptions in text

Definition Classes
Tokenizer
def setExceptionsPath(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("format" -> "text")): ChunkTokenizer.this.type
Path to txt file with list of token exceptions
Path to txt file with list of token exceptions

Definition Classes
Tokenizer

Packages

ChunkTokenizer 

Companion object ChunkTokenizer

class ChunkTokenizer extends Tokenizer

Example

Instance Constructors

Type Members

Value Members

Inherited from Tokenizer

Value Members

Inherited from AnnotatorApproach[TokenizerModel]

Value Members

Inherited from CanBeLazy

Value Members

Inherited from DefaultParamsWritable

Value Members

Inherited from MLWritable

Value Members

Inherited from HasOutputAnnotationCol

Value Members

Inherited from HasInputAnnotationCols

Value Members

Inherited from Estimator[TokenizerModel]

Value Members

Inherited from PipelineStage

Value Members

Inherited from Logging

Value Members

Inherited from Params

Value Members

Inherited from Identifiable

Value Members

Inherited from AnyRef

Value Members

Inherited from Any

Value Members

Parameters

Annotator types

Members

Parameter setters

Parameter getters

ChunkTokenizer