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c

com.johnsnowlabs.nlp

AnnotatorModel

abstract class AnnotatorModel[M <: Model[M]] extends Model[M] with RawAnnotator[M] with CanBeLazy

This trait implements logic that applies nlp using Spark ML Pipeline transformers Should strongly change once UsedDefinedTypes are allowed https://issues.apache.org/jira/browse/SPARK-7768

Linear Supertypes
CanBeLazy, RawAnnotator[M], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[M], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
OpenAICompletion, OpenAIEmbeddings, TableAssembler, TokenAssembler, Chunk2Doc, ChunkTokenizerModel, Chunker, Date2Chunk, DateMatcher, DocumentCharacterTextSplitter, DocumentNormalizer, DocumentTokenSplitter, GraphExtraction, LemmatizerModel, MultiDateMatcher, NGramGenerator, NormalizerModel, RecursiveTokenizerModel, RegexMatcherModel, RegexTokenizer, Stemmer, StopWordsCleaner, TextMatcherModel, Token2Chunk, TokenizerModel, HubertForCTC, Wav2Vec2ForCTC, WhisperForCTC, BigTextMatcherModel, AlbertForQuestionAnswering, AlbertForSequenceClassification, AlbertForTokenClassification, AlbertForZeroShotClassification, BartForZeroShotClassification, BertForMultipleChoice, BertForQuestionAnswering, BertForSequenceClassification, BertForTokenClassification, BertForZeroShotClassification, CamemBertForQuestionAnswering, CamemBertForSequenceClassification, CamemBertForTokenClassification, CamemBertForZeroShotClassification, ClassifierDLModel, DeBertaForQuestionAnswering, DeBertaForSequenceClassification, DeBertaForTokenClassification, DeBertaForZeroShotClassification, DistilBertForQuestionAnswering, DistilBertForSequenceClassification, DistilBertForTokenClassification, DistilBertForZeroShotClassification, LongformerForQuestionAnswering, LongformerForSequenceClassification, LongformerForTokenClassification, MPNetForQuestionAnswering, MPNetForSequenceClassification, MPNetForTokenClassification, MultiClassifierDLModel, RoBertaForQuestionAnswering, RoBertaForSequenceClassification, RoBertaForTokenClassification, RoBertaForZeroShotClassification, SentimentDLModel, TapasForQuestionAnswering, XlmRoBertaForQuestionAnswering, XlmRoBertaForSequenceClassification, XlmRoBertaForTokenClassification, XlmRoBertaForZeroShotClassification, XlnetForSequenceClassification, XlnetForTokenClassification, SpanBertCorefModel, CLIPForZeroShotClassification, ConvNextForImageClassification, SwinForImageClassification, ViTForImageClassification, VisionEncoderDecoderForImageCaptioning, EntityRulerModel, YakeKeywordExtraction, LanguageDetectorDL, NerConverter, NerOverwriter, NerCrfModel, NerDLModel, ZeroShotNerModel, DependencyParserModel, TypedDependencyParserModel, PerceptronModel, SentenceDetector, SentimentDetectorModel, ViveknSentimentModel, SentenceDetectorDLModel, AutoGGUFModel, BartTransformer, CPMTransformer, GPT2Transformer, LLAMA2Transformer, LLAMA3Transformer, M2M100Transformer, MarianTransformer, MistralTransformer, NLLBTransformer, Phi2Transformer, Phi3Transformer, QwenTransformer, StarCoderTransformer, T5Transformer, DocumentSimilarityRankerModel, ContextSpellCheckerModel, NorvigSweetingModel, SymmetricDeleteModel, WordSegmenterModel, AlbertEmbeddings, BGEEmbeddings, BertEmbeddings, BertSentenceEmbeddings, CamemBertEmbeddings, ChunkEmbeddings, DeBertaEmbeddings, DistilBertEmbeddings, Doc2VecModel, E5Embeddings, ElmoEmbeddings, InstructorEmbeddings, LongformerEmbeddings, MPNetEmbeddings, MxbaiEmbeddings, NomicEmbeddings, RoBertaEmbeddings, RoBertaSentenceEmbeddings, SentenceEmbeddings, SnowFlakeEmbeddings, UAEEmbeddings, UniversalSentenceEncoder, Word2VecModel, WordEmbeddingsModel, XlmRoBertaEmbeddings, XlmRoBertaSentenceEmbeddings, XlnetEmbeddings
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. AnnotatorModel
  2. CanBeLazy
  3. RawAnnotator
  4. HasOutputAnnotationCol
  5. HasInputAnnotationCols
  6. HasOutputAnnotatorType
  7. ParamsAndFeaturesWritable
  8. HasFeatures
  9. DefaultParamsWritable
  10. MLWritable
  11. Model
  12. Transformer
  13. PipelineStage
  14. Logging
  15. Params
  16. Serializable
  17. Serializable
  18. Identifiable
  19. AnyRef
  20. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new AnnotatorModel()

Type Members

  1. type AnnotationContent = Seq[Row]

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    Attributes
    protected
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Abstract Value Members

  1. abstract val inputAnnotatorTypes: Array[String]

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

    Definition Classes
    HasInputAnnotationCols
  2. abstract val outputAnnotatorType: AnnotatorType
    Definition Classes
    HasOutputAnnotatorType
  3. abstract val uid: String
    Definition Classes
    Identifiable

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
  11. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  12. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
  13. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  14. final def clear(param: Param[_]): AnnotatorModel.this.type
    Definition Classes
    Params
  15. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  16. def copy(extra: ParamMap): M

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  17. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  18. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  19. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  21. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  22. def explainParams(): String
    Definition Classes
    Params
  23. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  24. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  25. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  26. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  27. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  28. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  29. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  30. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  31. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  32. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  33. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  34. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  35. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  36. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  37. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  38. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  39. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  40. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  41. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  42. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  43. def hasParent: Boolean
    Definition Classes
    Model
  44. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  45. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  46. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  47. 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
  48. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  49. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  50. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  51. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  52. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  53. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  54. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  61. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  66. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  67. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  68. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  69. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  70. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  71. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  72. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  73. var parent: Estimator[M]
    Definition Classes
    Model
  74. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  75. def set[T](feature: StructFeature[T], value: T): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  76. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  77. def set[T](feature: SetFeature[T], value: Set[T]): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  78. def set[T](feature: ArrayFeature[T], value: Array[T]): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  79. final def set(paramPair: ParamPair[_]): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  80. final def set(param: String, value: Any): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  81. final def set[T](param: Param[T], value: T): AnnotatorModel.this.type
    Definition Classes
    Params
  82. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  83. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  84. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  85. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  86. final def setDefault(paramPairs: ParamPair[_]*): AnnotatorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  87. final def setDefault[T](param: Param[T], value: T): AnnotatorModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  88. final def setInputCols(value: String*): AnnotatorModel.this.type
    Definition Classes
    HasInputAnnotationCols
  89. def setInputCols(value: Array[String]): AnnotatorModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  90. def setLazyAnnotator(value: Boolean): AnnotatorModel.this.type
    Definition Classes
    CanBeLazy
  91. final def setOutputCol(value: String): AnnotatorModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  92. def setParent(parent: Estimator[M]): M
    Definition Classes
    Model
  93. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  94. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  95. final def transform(dataset: Dataset[_]): DataFrame

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    dataset

    Dataset[Row]

    Definition Classes
    AnnotatorModel → Transformer
  96. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  97. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  98. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    RawAnnotator → PipelineStage
  99. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  100. 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
    RawAnnotator
  101. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  102. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  103. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  104. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  105. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from CanBeLazy

Inherited from RawAnnotator[M]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[M]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped