object NerTagged extends Tagged[NerTaggedSentence]
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def
collectLabeledInstances(dataset: Dataset[Row], taggedCols: Seq[String], labelColumn: String): Array[(TextSentenceLabels, NerTaggedSentence)]
Method is usefull for testing.
Method is usefull for testing.
- dataset
dataset row
- taggedCols
list of tagged columns
- labelColumn
label column
- Definition Classes
- Tagged
- def collectTrainingInstancesWithPos(dataset: Dataset[Row], posTaggedCols: Seq[String], labelColumn: String): Array[(TextSentenceLabels, PosTaggedSentence, WordpieceEmbeddingsSentence)]
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val
emptyTag: String
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def
getAnnotations(row: Row, colNum: Int): Seq[Annotation]
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def
getClass(): Class[_]
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def
getLabelsFromSentences(sentences: Seq[WordpieceEmbeddingsSentence], labelAnnotations: Seq[Annotation]): Seq[TextSentenceLabels]
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def
getLabelsFromTaggedSentences(sentences: Seq[TaggedSentence], labelAnnotations: Seq[Annotation]): Seq[TextSentenceLabels]
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def
iterateOnArray(inputArray: Array[Row], sentenceCols: Seq[String], batchSize: Int): Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]]
FIXME: ColNums not always in the given order
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def
iterateOnDataframe(dataset: Dataset[Row], sentenceCols: Seq[String], labelColumn: String, batchSize: Int): Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]]
FIXME: ColNums not always in the given order
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def
notifyAll(): Unit
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- def pack(items: Seq[NerTaggedSentence]): Seq[Annotation]
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def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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- def unpack(annotations: Seq[Annotation]): Seq[NerTaggedSentence]
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