case class PubTator() extends Product with Serializable
The PubTator format includes medical papers’ titles, abstracts, and tagged chunks.
For more information see PubTator Docs and MedMentions Docs.
readDataset
is used to create a Spark DataFrame from a PubTator text file.
Example
import com.johnsnowlabs.nlp.training.PubTator val pubTatorFile = "./src/test/resources/corpus_pubtator_sample.txt" val pubTatorDataSet = PubTator().readDataset(ResourceHelper.spark, pubTatorFile) pubTatorDataSet.show(1) +--------+--------------------+--------------------+--------------------+-----------------------+---------------------+-----------------------+ | doc_id| finished_token| finished_pos| finished_ner|finished_token_metadata|finished_pos_metadata|finished_label_metadata| +--------+--------------------+--------------------+--------------------+-----------------------+---------------------+-----------------------+ |25763772|[DCTN4, as, a, mo...|[NNP, IN, DT, NN,...|[B-T116, O, O, O,...| [[sentence, 0], [...| [[word, DCTN4], [...| [[word, DCTN4], [...| +--------+--------------------+--------------------+--------------------+-----------------------+---------------------+-----------------------+
Linear Supertypes
Ordering
- Alphabetic
- By Inheritance
Inherited
- PubTator
- Serializable
- Serializable
- Product
- Equals
- AnyRef
- Any
- Hide All
- Show All
Visibility
- Public
- All
Instance Constructors
- new PubTator()
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
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
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()
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
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 readDataset(spark: SparkSession, path: String, isPaddedToken: Boolean = true): DataFrame
-
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()