class ChunkMergeApproach extends AnnotatorApproach[ChunkMergeModel] with CheckLicense with HasMultipleInputAnnotationCols with MergeResourceParams with MergeCommonParams with MergePrioritizationParams with HasFeatures with FilteringParams with HandleExceptionParams with ResetSentenceIndicesParam
Merges two chunk columns coming from two annotators(NER, ContextualParser or any other annotator producing chunks). The merger of the two chunk columns is made by selecting one chunk from one of the columns according to certain criteria. The decision on which chunk to select is made according to the chunk indices in the source document. (chunks with longer lengths and highest information will be kept from each source) Labels can be changed by setReplaceDictResource.
Example
Define a pipeline with 2 different NER models with a ChunkMergeApproach at the end
val data = Seq(("A 63-year-old man presents to the hospital ...")).toDF("text") val pipeline = new Pipeline().setStages(Array( new DocumentAssembler().setInputCol("text").setOutputCol("document"), new SentenceDetector().setInputCols("document").setOutputCol("sentence"), new Tokenizer().setInputCols("sentence").setOutputCol("token"), WordEmbeddingsModel.pretrained("embeddings_clinical", "en", "clinical/models").setOutputCol("embs"), MedicalNerModel.pretrained("ner_jsl", "en", "clinical/models") .setInputCols("sentence", "token", "embs").setOutputCol("jsl_ner"), new NerConverter().setInputCols("sentence", "token", "jsl_ner").setOutputCol("jsl_ner_chunk"), MedicalNerModel.pretrained("ner_bionlp", "en", "clinical/models") .setInputCols("sentence", "token", "embs").setOutputCol("bionlp_ner"), new NerConverter().setInputCols("sentence", "token", "bionlp_ner") .setOutputCol("bionlp_ner_chunk"), new ChunkMergeApproach().setInputCols("jsl_ner_chunk", "bionlp_ner_chunk").setOutputCol("merged_chunk") ))
Show results
val result = pipeline.fit(data).transform(data).cache() result.selectExpr("explode(merged_chunk) as a") .selectExpr("a.begin","a.end","a.result as chunk","a.metadata.entity as entity") .show(5, false) +-----+---+-----------+---------+ |begin|end|chunk |entity | +-----+---+-----------+---------+ |5 |15 |63-year-old|Age | |17 |19 |man |Gender | |64 |72 |recurrent |Modifier | |98 |107|cellulitis |Diagnosis| |110 |119|pneumonias |Diagnosis| +-----+---+-----------+---------+
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- ChunkMergeApproach
- ResetSentenceIndicesParam
- HandleExceptionParams
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- MergePrioritizationParams
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- HasMultipleInputAnnotationCols
- CheckLicense
- AnnotatorApproach
- CanBeLazy
- DefaultParamsWritable
- MLWritable
- HasOutputAnnotatorType
- HasOutputAnnotationCol
- HasInputAnnotationCols
- Estimator
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Type Members
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type
AnnotatorType = String
- Definition Classes
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Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
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final
def
##(): Int
- Definition Classes
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final
def
$[T](param: Param[T]): T
- Attributes
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def
$$[T](feature: StructFeature[T]): T
- Attributes
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def
$$[K, V](feature: MapFeature[K, V]): Map[K, V]
- Attributes
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def
$$[T](feature: SetFeature[T]): Set[T]
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def
$$[T](feature: ArrayFeature[T]): Array[T]
- Attributes
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final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
_fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): ChunkMergeModel
- Attributes
- protected
- Definition Classes
- AnnotatorApproach
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
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def
beforeTraining(spark: SparkSession): Unit
- Definition Classes
- AnnotatorApproach
-
val
blackList: StringArrayParam
If defined, list of entities to ignore.
If defined, list of entities to ignore. The rest will be processed
- Definition Classes
- FilteringParams
-
val
caseSensitive: BooleanParam
Determines whether the definitions of the white listed and black listed entities are case sensitive or not.
Determines whether the definitions of the white listed and black listed entities are case sensitive or not. If the filterValue is 'entity', 'caseSensitive' is always false. The default value is true, except: com.johnsnowlabs.nlp.annotators.chunker.AssertionFilterer
- Definition Classes
- FilteringParams
-
final
def
checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
-
def
checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
- Definition Classes
- CheckLicense
-
def
checkValidScope(scope: String): Unit
- Definition Classes
- CheckLicense
-
def
checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
- Definition Classes
- CheckLicense
-
def
checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
- Definition Classes
- CheckLicense
-
val
chunkPrecedence: Param[String]
When ChunkPrecedence ordering feature is used this param contains the comma separated metadata fields that drive prioritization of overlapping annotations.
When ChunkPrecedence ordering feature is used this param contains the comma separated metadata fields that drive prioritization of overlapping annotations. When used by itself (empty chunkPrecedenceValuePrioritization) annotations will be prioritized based on number of metadata fields present. When used together with chunkPrecedenceValuePrioritization param it will prioritize based on the order of its values.
- Definition Classes
- MergePrioritizationParams
-
val
chunkPrecedenceValuePrioritization: StringArrayParam
When ChunkPrecedence ordering feature is used this param contains an Array of comma separated strings representing the desired order of prioritization for the values in the metadata fields included in chunkPrecedence.
When ChunkPrecedence ordering feature is used this param contains an Array of comma separated strings representing the desired order of prioritization for the values in the metadata fields included in chunkPrecedence.
- Definition Classes
- MergePrioritizationParams
-
final
def
clear(param: Param[_]): ChunkMergeApproach.this.type
- Definition Classes
- Params
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
final
def
copy(extra: ParamMap): Estimator[ChunkMergeModel]
- Definition Classes
- AnnotatorApproach → Estimator → PipelineStage → Params
-
def
copyValues[T <: Params](to: T, extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
val
criteria: Param[String]
It is used to how to compare black and white listed values with the result of the Annotation.
It is used to how to compare black and white listed values with the result of the Annotation. Possible values are the following: 'isin', 'regex'. Default: isin
- isin : Filter by the chunk
- regex : Filter by using a regex
- Definition Classes
- FilteringParams
-
val
defaultConfidence: FloatParam
When ChunkConfidence ordering feature is included and a given annotation does not have any confidence the value of this param will be used.
When ChunkConfidence ordering feature is included and a given annotation does not have any confidence the value of this param will be used.
- Definition Classes
- MergePrioritizationParams
-
final
def
defaultCopy[T <: Params](extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
val
description: String
- Definition Classes
- ChunkMergeApproach → AnnotatorApproach
-
val
doExceptionHandling: BooleanParam
If true, exceptions are handled.
If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.
- Definition Classes
- HandleExceptionParams
-
val
entitiesConfidence: MapFeature[String, Float]
Pairs (entity,confidenceThreshold).
Pairs (entity,confidenceThreshold). Filter the chunks with entities which have confidence lower than the confidence threshold.
- Definition Classes
- FilteringParams
-
lazy val
entitiesConfidenceMap: Map[String, Float]
- Definition Classes
- FilteringParams
-
val
entitiesConfidenceResource: ExternalResourceParam
Path to csv with entity pairs to remove chunks based on the confidance level
Path to csv with entity pairs to remove chunks based on the confidance level
- Definition Classes
- MergeResourceParams
-
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
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final
def
extractParamMap(): ParamMap
- Definition Classes
- Params
-
final
def
extractParamMap(extra: ParamMap): ParamMap
- Definition Classes
- Params
-
val
falsePositivesResource: ExternalResourceParam
Path to csv with false positive text, entity pairs to remove
Path to csv with false positive text, entity pairs to remove
- Definition Classes
- MergeResourceParams
-
val
features: ArrayBuffer[Feature[_, _, _]]
- Definition Classes
- HasFeatures
-
val
filterValue: Param[String]
Possible values are 'result' and 'entity'.
Possible values are 'result' and 'entity'. If the value is 'entity', it filters the ner chunks by the ner label that you want to filter. If the value is 'result', it will filter chunks by the result of the Annotation.
- Definition Classes
- FilteringParams
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
final
def
fit(dataset: Dataset[_]): ChunkMergeModel
- Definition Classes
- AnnotatorApproach → Estimator
-
def
fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[ChunkMergeModel]
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" )
-
def
fit(dataset: Dataset[_], paramMap: ParamMap): ChunkMergeModel
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" )
-
def
fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ChunkMergeModel
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" ) @varargs()
-
def
get[T](feature: StructFeature[T]): Option[T]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
get[T](feature: SetFeature[T]): Option[Set[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
get[T](feature: ArrayFeature[T]): Option[Array[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getBlackList: Array[String]
Gets blackList parameter
Gets blackList parameter
- Definition Classes
- FilteringParams
-
def
getCaseSensitive: Boolean
Gets caseSensitive parameter
Gets caseSensitive parameter
- Definition Classes
- FilteringParams
-
def
getChunkPrecedence: String
- Definition Classes
- MergePrioritizationParams
-
def
getChunkPrecedenceValuePrioritization: Array[String]
- Definition Classes
- MergePrioritizationParams
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getDefaultConfidence: Float
- Definition Classes
- MergePrioritizationParams
-
def
getInputCols: Array[String]
- Definition Classes
- HasInputAnnotationCols
-
def
getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
-
def
getMergeOverlapping: Boolean
- Definition Classes
- MergeCommonParams
-
final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
-
def
getOrderingFeatures: Array[String]
- Definition Classes
- MergePrioritizationParams
-
final
def
getOutputCol: String
- Definition Classes
- HasOutputAnnotationCol
-
def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
-
def
getResetSentenceIndices: Boolean
Gets resetSentenceIndices parameter
Gets resetSentenceIndices parameter
- Definition Classes
- ResetSentenceIndicesParam
-
def
getSelectionStrategy: String
- Definition Classes
- MergePrioritizationParams
-
def
getWhiteList: Array[String]
Gets whiteList parameter
Gets whiteList parameter
- Definition Classes
- FilteringParams
-
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
-
val
inputAnnotatorType: String
Output annotator types: CHUNK, CHUNK
Output annotator types: CHUNK, CHUNK
- Definition Classes
- ChunkMergeApproach → HasMultipleInputAnnotationCols
-
lazy val
inputAnnotatorTypes: Array[String]
- Definition Classes
- HasMultipleInputAnnotationCols → HasInputAnnotationCols
-
final
val
inputCols: StringArrayParam
- 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
mergeOverlapping: BooleanParam
whether to merge overlapping matched chunks.
whether to merge overlapping matched chunks. Defaults to true
- Definition Classes
- MergeCommonParams
-
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: ChunkMergeModel, spark: SparkSession): Unit
- Definition Classes
- AnnotatorApproach
-
val
optionalInputAnnotatorTypes: Array[String]
- Definition Classes
- HasInputAnnotationCols
-
val
orderingFeatures: StringArrayParam
Array of strings specifying the ordering features to use for overlapping entities.
Array of strings specifying the ordering features to use for overlapping entities. Possible values are ChunkBegin, ChunkLength, ChunkPrecedence, ChunkConfidence.
- Definition Classes
- MergePrioritizationParams
-
val
outputAnnotatorType: AnnotatorType
Input annotator types: CHUNK
Input annotator types: CHUNK
- Definition Classes
- ChunkMergeApproach → HasOutputAnnotatorType
-
final
val
outputCol: Param[String]
- Attributes
- protected
- Definition Classes
- HasOutputAnnotationCol
-
lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
def
prioritize(annotations: Seq[Annotation]): Seq[Annotation]
- Attributes
- protected
- Definition Classes
- MergePrioritizationParams
-
val
regex: StringArrayParam
If defined, list of regex to process the chunks (Default:
Array()
)If defined, list of regex to process the chunks (Default:
Array()
)- Definition Classes
- FilteringParams
-
val
replaceDictResource: ExternalResourceParam
dictionary with regular expression patterns that match some protected entity TODO: is this regex?
dictionary with regular expression patterns that match some protected entity TODO: is this regex?
- Definition Classes
- MergeResourceParams
-
def
resetSentenceIndices(metadata: Map[String, String]): Map[String, String]
Reset sentence index in metadata by adding
"sentence" -> "0"
Reset sentence index in metadata by adding
"sentence" -> "0"
- Attributes
- protected
- Definition Classes
- ResetSentenceIndicesParam
-
val
resetSentenceIndices: BooleanParam
Whether to reset sentence indices to treat the entire output as if it originates from a single document.
Whether to reset sentence indices to treat the entire output as if it originates from a single document.
When set to true, the metadata of each entity will be updated by assigning the
sentence
key a value of0
, effectively treating the entire output as if it comes from a single document, regardless of the original sentence boundaries. Default: False.- Definition Classes
- ResetSentenceIndicesParam
-
def
resolveFilter(chunkerAnnotations: Seq[Annotation]): Seq[Annotation]
- Attributes
- protected
- Definition Classes
- FilteringParams
-
def
resolveMergeFilter(a: Annotation, entityValue: String, falsePositivesArray: Array[(String, String, String)], replaceDictMap: Map[String, String] = Map.empty): Option[Annotation]
- Attributes
- protected
- Definition Classes
- FilteringParams
-
def
resolveWhiteListBlackListFilter(annotations: Seq[Annotation]): Seq[Annotation]
- Attributes
- protected
- Definition Classes
- FilteringParams
-
def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
-
val
selectionStrategy: Param[String]
Whether to select annotations sequentially based on annotation order (Sequential) or using any other available strategy; currently only Sequential and DiverseLonger are available.
Whether to select annotations sequentially based on annotation order (Sequential) or using any other available strategy; currently only Sequential and DiverseLonger are available.
- Definition Classes
- MergePrioritizationParams
-
def
set[T](feature: StructFeature[T], value: T): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[K, V](feature: MapFeature[K, V], value: Map[K, V]): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: SetFeature[T], value: Set[T]): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: ArrayFeature[T], value: Array[T]): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
set(paramPair: ParamPair[_]): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set(param: String, value: Any): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set[T](param: Param[T], value: T): ChunkMergeApproach.this.type
- Definition Classes
- Params
-
def
setAllowList(list: String*): ChunkMergeApproach.this.type
- Definition Classes
- FilteringParams
-
def
setAllowList(list: Array[String]): ChunkMergeApproach.this.type
- Definition Classes
- FilteringParams
-
def
setBlackList(list: String*): ChunkMergeApproach.this.type
- Definition Classes
- FilteringParams
-
def
setBlackList(list: Array[String]): ChunkMergeApproach.this.type
If defined, list of entities to ignore.
If defined, list of entities to ignore. The rest will be processed.
- Definition Classes
- FilteringParams
-
def
setCaseSensitive(value: Boolean): ChunkMergeApproach.this.type
Determines whether the definitions of the white listed and black listed entities are case sensitive or not.
Determines whether the definitions of the white listed and black listed entities are case sensitive or not. If the filterValue is 'entity', 'caseSensitive' is always False. The default value is true, except: com.johnsnowlabs.nlp.annotators.chunker.AssertionFilterer
- Definition Classes
- FilteringParams
-
def
setChunkPrecedence(m: String): ChunkMergeApproach.this.type
- Definition Classes
- MergePrioritizationParams
-
def
setChunkPrecedenceValuePrioritization(m: Array[String]): ChunkMergeApproach.this.type
- Definition Classes
- MergePrioritizationParams
-
def
setCriteria(s: String): ChunkMergeApproach.this.type
Sets criteria for how to compare black and white listed values with the result of the Annotation.
Sets criteria for how to compare black and white listed values with the result of the Annotation. Possible values are the following: 'isin', 'regex'. Default: isin.
- 'isin' : Filter by the chunk.
- 'regex' : Filter by using a regex.
- You can use 'assertion' in com.johnsnowlabs.nlp.annotators.chunker.AssertionFilterer and 'assertion' option is default value for com.johnsnowlabs.nlp.annotators.chunker.AssertionFilterer
- Definition Classes
- FilteringParams
-
def
setDefault[T](feature: StructFeature[T], value: () ⇒ T): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
setDefault(paramPairs: ParamPair[_]*): ChunkMergeApproach.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
setDefault[T](param: Param[T], value: T): ChunkMergeApproach.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
-
def
setDefaultConfidence(m: Float): ChunkMergeApproach.this.type
- Definition Classes
- MergePrioritizationParams
-
def
setDenyList(list: String*): ChunkMergeApproach.this.type
- Definition Classes
- FilteringParams
-
def
setDenyList(list: Array[String]): ChunkMergeApproach.this.type
- Definition Classes
- FilteringParams
-
def
setDoExceptionHandling(value: Boolean): ChunkMergeApproach.this.type
If true, exceptions are handled.
If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.
- Definition Classes
- HandleExceptionParams
-
def
setEntitiesConfidence(value: HashMap[String, Double]): ChunkMergeApproach.this.type
Sets Pairs (entity,confidenceThreshold) to filter the chunks with entities which have confidence lower than the confidence threshold.
-
def
setEntitiesConfidence(value: Map[String, Float]): ChunkMergeApproach.this.type
- Definition Classes
- FilteringParams
-
def
setEntitiesConfidenceResource(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("delimiter" -> ",")): ChunkMergeApproach.this.type
- Definition Classes
- MergeResourceParams
-
def
setFalsePositivesResource(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("delimiter" -> ",")): ChunkMergeApproach.this.type
Path to csv with false positive text, entity pairs to remove
Path to csv with false positive text, entity pairs to remove
- Definition Classes
- MergeResourceParams
-
def
setFilterEntity(v: String): ChunkMergeApproach.this.type
Possible values are 'result' and 'entity'.
Possible values are 'result' and 'entity'. If the value is 'entity', it filters the ner chunks by the ner label that you want to filter. If the value is 'result', it will filter chunks by the result of the Annotation.
- Definition Classes
- FilteringParams
-
def
setInputCols(value: Array[String]): ChunkMergeApproach.this.type
- Definition Classes
- HasMultipleInputAnnotationCols → HasInputAnnotationCols
-
final
def
setInputCols(value: String*): ChunkMergeApproach.this.type
- Definition Classes
- HasInputAnnotationCols
-
def
setLazyAnnotator(value: Boolean): ChunkMergeApproach.this.type
- Definition Classes
- CanBeLazy
-
def
setMergeOverlapping(v: Boolean): ChunkMergeApproach.this.type
whether to merge overlapping matched chunks.
whether to merge overlapping matched chunks.
- Definition Classes
- MergeCommonParams
-
def
setOrderingFeatures(m: Array[String]): ChunkMergeApproach.this.type
- Definition Classes
- MergePrioritizationParams
-
final
def
setOutputCol(value: String): ChunkMergeApproach.this.type
- Definition Classes
- HasOutputAnnotationCol
-
def
setRegex(list: String*): ChunkMergeApproach.this.type
Sets the list of regexes to process the chunks.
Sets the list of regexes to process the chunks.
- Definition Classes
- FilteringParams
-
def
setReplaceDictResource(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("delimiter" -> ",")): ChunkMergeApproach.this.type
dictionary with regular expression patterns that match some protected entity
dictionary with regular expression patterns that match some protected entity
- Definition Classes
- MergeResourceParams
-
def
setReplaceDictResource(path: ExternalResource): ChunkMergeApproach.this.type
dictionary with regular expression patterns that match some protected entity
dictionary with regular expression patterns that match some protected entity
- Definition Classes
- MergeResourceParams
-
def
setResetSentenceIndices(value: Boolean): ChunkMergeApproach.this.type
Set whether to reset sentence indices to treat the entire output as if it originates from a single document.
Set whether to reset sentence indices to treat the entire output as if it originates from a single document.
When set to true, the metadata of each entity will be updated by assigning the
sentence
key a value of0
, effectively treating the entire output as if it comes from a single document, regardless of the original sentence boundaries. Default: False.- Definition Classes
- ResetSentenceIndicesParam
-
def
setSelectionStrategy(m: String): ChunkMergeApproach.this.type
- Definition Classes
- MergePrioritizationParams
-
def
setWhiteList(list: String*): ChunkMergeApproach.this.type
- Definition Classes
- FilteringParams
-
def
setWhiteList(list: Array[String]): ChunkMergeApproach.this.type
Sets the list of entities to process.
Sets the list of entities to process. The rest will be ignored. Do not include IOB prefix on labels.
- Definition Classes
- FilteringParams
-
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]): ChunkMergeModel
Trains a model from the provided dataset.
Trains a model from the provided dataset. Input columns should be set to output columns from e.g. a NerDLModel and a RegexMatcher.
- Definition Classes
- ChunkMergeApproach → AnnotatorApproach
-
def
transformEntitiesConfidenceResource(): Map[String, Float]
- Attributes
- protected
- Definition Classes
- MergeResourceParams
-
def
transformFalsePositivesResource(): Array[(String, String, String)]
- Attributes
- protected
- Definition Classes
- MergeResourceParams
- def transformReplaceDict(replaceDict: Array[(String, String)]): Map[String, String]
-
def
transformReplaceDictResource(): Array[(String, String)]
- Attributes
- protected
- Definition Classes
- MergeResourceParams
-
final
def
transformSchema(schema: StructType): StructType
- Definition Classes
- AnnotatorApproach → PipelineStage
-
def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
-
val
uid: String
- Definition Classes
- ChunkMergeApproach → Identifiable
-
def
validate(schema: StructType): Boolean
- 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()
-
val
whiteList: StringArrayParam
If defined, list of entities to process.
If defined, list of entities to process. The rest will be ignored. Does not include IOB prefix on labels (Default:
Array()
)- Definition Classes
- FilteringParams
-
def
write: MLWriter
- Definition Classes
- DefaultParamsWritable → MLWritable
Inherited from ResetSentenceIndicesParam
Inherited from HandleExceptionParams
Inherited from FilteringParams
Inherited from HasFeatures
Inherited from MergePrioritizationParams
Inherited from MergeCommonParams
Inherited from MergeResourceParams
Inherited from HasMultipleInputAnnotationCols
Inherited from CheckLicense
Inherited from AnnotatorApproach[ChunkMergeModel]
Inherited from CanBeLazy
Inherited from DefaultParamsWritable
Inherited from MLWritable
Inherited from HasOutputAnnotatorType
Inherited from HasOutputAnnotationCol
Inherited from HasInputAnnotationCols
Inherited from Estimator[ChunkMergeModel]
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