Packages

class AssertionDLModel extends AnnotatorModel[AssertionDLModel] with WriteTensorflowModel with HasStorageRef with HasSimpleAnnotate[AssertionDLModel] with ParamsAndFeaturesWritable with CheckLicense

This is a main class in AssertionDL family. A Deep Learning based approach is used to extract Assertion Status from extracted entities and text. AssertionDLModel requires DOCUMENT, CHUNK and WORD_EMBEDDINGS type annotator inputs, which can be obtained by e.g a DocumentAssembler, NerConverter and WordEmbeddingsModel. The result is an assertion status annotation for each recognized entity. Possible values include “present”, “absent”, “hypothetical”, “conditional”, “associated_with_other_person” etc.

For pretrained models please see the Models Hub for available models.

Example

Define pipeline stages to extract NER chunks first

val data = Seq(
  "Patient with severe fever and sore throat",
  "Patient shows no stomach pain",
  "She was maintained on an epidural and PCA for pain control.").toDF("text")
val documentAssembler = new DocumentAssembler().setInputCol("text").setOutputCol("document")
val sentenceDetector = new SentenceDetector().setInputCols("document").setOutputCol("sentence")
val tokenizer = new Tokenizer().setInputCols("sentence").setOutputCol("token")
val embeddings = WordEmbeddingsModel.pretrained("embeddings_clinical", "en", "clinical/models")
  .setOutputCol("embeddings")
val nerModel = MedicalNerModel.pretrained("ner_clinical", "en", "clinical/models")
  .setInputCols("sentence", "token", "embeddings").setOutputCol("ner")
val nerConverter = new NerConverter().setInputCols("sentence", "token", "ner").setOutputCol("ner_chunk")

Then a pretrained AssertionDLModel is used to extract the assertion status

val clinicalAssertion = AssertionDLModel.pretrained("assertion_dl", "en", "clinical/models")
  .setInputCols("sentence", "ner_chunk", "embeddings")
  .setOutputCol("assertion")

val assertionPipeline = new Pipeline().setStages(Array(
  documentAssembler,
  sentenceDetector,
  tokenizer,
  embeddings,
  nerModel,
  nerConverter,
  clinicalAssertion
))

val assertionModel = assertionPipeline.fit(data)

Show results

val result = assertionModel.transform(data)
result.selectExpr("ner_chunk.result", "assertion.result").show(3, truncate=false)
+--------------------------------+--------------------------------+
|result                          |result                          |
+--------------------------------+--------------------------------+
|[severe fever, sore throat]     |[present, present]              |
|[stomach pain]                  |[absent]                        |
|[an epidural, PCA, pain control]|[present, present, hypothetical]|
+--------------------------------+--------------------------------+
See also

AssertionDLApproach for training a custom AssertionDLModel

AssertionLogRegModel for non deep learning based extraction

Linear Supertypes
CheckLicense, HasSimpleAnnotate[AssertionDLModel], HasStorageRef, WriteTensorflowModel, AnnotatorModel[AssertionDLModel], CanBeLazy, RawAnnotator[AssertionDLModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[AssertionDLModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. AssertionDLModel
  2. CheckLicense
  3. HasSimpleAnnotate
  4. HasStorageRef
  5. WriteTensorflowModel
  6. AnnotatorModel
  7. CanBeLazy
  8. RawAnnotator
  9. HasOutputAnnotationCol
  10. HasInputAnnotationCols
  11. HasOutputAnnotatorType
  12. ParamsAndFeaturesWritable
  13. HasFeatures
  14. DefaultParamsWritable
  15. MLWritable
  16. Model
  17. Transformer
  18. PipelineStage
  19. Logging
  20. Params
  21. Serializable
  22. Serializable
  23. Identifiable
  24. AnyRef
  25. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new AssertionDLModel()
  2. new AssertionDLModel(uid: String)

    uid

    a unique identifier for the instantiated AnnotatorModel

Type Members

  1. type AnnotationContent = Seq[Row]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

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
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

    This is main point of interest.

    This is main point of interest. It annotates the input dataset applying properties of the class above This method utilises chunk groups, word piece embeddings and conversion to chunk indexes

    annotations

    a sequence of Annotations

    returns

    a sequence of projected Annotations

    Definition Classes
    AssertionDLModel → HasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. val batchSize: IntParam

    Size of every batch

  14. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]

    This method validates the dataset before annotation

    This method validates the dataset before annotation

    dataset

    a collection of inputs to validate

    returns

    a Dataset after validation

    Attributes
    protected
    Definition Classes
    AssertionDLModel → AnnotatorModel
  15. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  16. def checkValidEnvironment(spark: Option[SparkContext]): Unit
    Definition Classes
    CheckLicense
  17. def checkValidScope(scope: String): Unit
    Definition Classes
    CheckLicense
  18. def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkContext], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  19. val classes: StringArrayParam

    List of internal copies of classes used to train for Python

  20. final def clear(param: Param[_]): AssertionDLModel.this.type
    Definition Classes
    Params
  21. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  22. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString Example Python code with TF version 2.3: In [1]: import tensorflow as tf In [2]: config = tf.compat.v1.ConfigProto(allow_soft_placement=True, log_device_placement=True) ...: config.gpu_options.allow_growth = True ...: for b in config.SerializeToString(): ...: print(b) ...: 50 2 32 1 56 1 64 1

  23. def copy(extra: ParamMap): AssertionDLModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    AssertionDLModel → RawAnnotator → Model → Transformer → PipelineStage → Params
  24. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  25. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  26. val datasetParams: StructFeature[DatasetEncoderParams]

    Collection of Parameters, which are used by method annotate()

  27. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  28. def dfAnnotate: UserDefinedFunction
    Definition Classes
    HasSimpleAnnotate
  29. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  30. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  31. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  32. def explainParams(): String
    Definition Classes
    Params
  33. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  34. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  35. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  36. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  37. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  38. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  39. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  40. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  42. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  43. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  44. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  45. def getClasses: Array[String]

    get the tags used to trained this NerDLModel

  46. def getConfigProtoBytes: Option[Array[Byte]]

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString

  47. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  48. def getIncludeConfidence: Boolean

    whether to include confidence scores in annotation metadata

  49. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  50. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  51. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  52. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  53. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  54. def getStorageRef: String
    Definition Classes
    HasStorageRef
  55. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  56. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  57. def hasParent: Boolean
    Definition Classes
    Model
  58. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  59. val includeConfidence: BooleanParam

    whether to include confidence scores in annotation metadata (Default: false)

  60. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  61. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. val inputAnnotatorTypes: Array[String]

    Input annotator types: DOCUMENT, CHUNK, WORD_EMBEDDINGS

    Input annotator types: DOCUMENT, CHUNK, WORD_EMBEDDINGS

    Definition Classes
    AssertionDLModel → HasInputAnnotationCols
  63. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  64. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  65. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  66. def isLp(): Boolean
    Definition Classes
    CheckLicense
  67. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  68. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  69. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  70. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  71. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  78. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  81. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. val maxSentLen: IntParam

    Max possible length of a sentence (Default: 256)

  83. def model: TensorflowAssertion

    Tensorflow model for the AssertionDLModel.

    Tensorflow model for the AssertionDLModel. This is used to generate the predictions.

  84. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  85. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  86. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  87. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  88. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    AssertionDLModel → ParamsAndFeaturesWritable
  89. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  90. val outputAnnotatorType: AnnotatorType

    Output annotator types: ASSERTION

    Output annotator types: ASSERTION

    Definition Classes
    AssertionDLModel → HasOutputAnnotatorType
  91. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  92. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  93. var parent: Estimator[AssertionDLModel]
    Definition Classes
    Model
  94. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  95. def set[T](feature: StructFeature[T], value: T): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  96. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  97. def set[T](feature: SetFeature[T], value: Set[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  98. def set[T](feature: ArrayFeature[T], value: Array[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  99. final def set(paramPair: ParamPair[_]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  100. final def set(param: String, value: Any): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  101. final def set[T](param: Param[T], value: T): AssertionDLModel.this.type
    Definition Classes
    Params
  102. def setBatchSize(size: Int): AssertionDLModel.this.type

    Size of every batch

  103. def setConfigProtoBytes(bytes: Array[Int]): AssertionDLModel

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString

  104. def setDatasetParams(params: DatasetEncoderParams): AssertionDLModel

    Collection of Parameters, which are used by method annotate()

  105. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  106. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  107. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  109. final def setDefault(paramPairs: ParamPair[_]*): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  110. final def setDefault[T](param: Param[T], value: T): AssertionDLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  111. def setIncludeConfidence(value: Boolean): AssertionDLModel.this.type

    whether to include confidence scores in annotation metadata

  112. final def setInputCols(value: String*): AssertionDLModel.this.type
    Definition Classes
    HasInputAnnotationCols
  113. final def setInputCols(value: Array[String]): AssertionDLModel.this.type
    Definition Classes
    HasInputAnnotationCols
  114. def setLazyAnnotator(value: Boolean): AssertionDLModel.this.type
    Definition Classes
    CanBeLazy
  115. def setMaxSentLen(len: Int): AssertionDLModel.this.type

    Max possible length of a sentence.

  116. final def setOutputCol(value: String): AssertionDLModel.this.type
    Definition Classes
    HasOutputAnnotationCol
  117. def setParent(parent: Estimator[AssertionDLModel]): AssertionDLModel
    Definition Classes
    Model
  118. def setStorageRef(value: String): AssertionDLModel.this.type
    Definition Classes
    HasStorageRef
  119. def setTensorflow(spark: SparkSession, tf: TensorflowWrapper): AssertionDLModel
  120. val storageRef: Param[String]
    Definition Classes
    HasStorageRef
  121. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  122. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  123. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  124. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  125. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  126. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  127. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  128. val uid: String
    Definition Classes
    AssertionDLModel → Identifiable
  129. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  130. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  131. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  132. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  133. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  134. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  135. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  136. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  137. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  138. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]], savedSignatures: Option[Map[String, String]]): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from CheckLicense

Inherited from HasSimpleAnnotate[AssertionDLModel]

Inherited from HasStorageRef

Inherited from WriteTensorflowModel

Inherited from AnnotatorModel[AssertionDLModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[AssertionDLModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[AssertionDLModel]

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

Parameters

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters