com.johnsnowlabs.nlp.annotators.sentence_detector_dl
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
takes a document and annotations and produces new annotations of this annotator's annotation type
takes a document and annotations and produces new annotations of this annotator's annotation type
Annotations that correspond to inputAnnotationCols generated by previous annotators if any
any number of annotations processed for every input annotation. Not necessary one to one relationship
requirement for annotators copies
requirement for annotators copies
characters used to explicitly mark sentence bounds
Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column
Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column
udf function to be applied to inputCols using this annotator's annotate function as part of ML transformation
A flag indicating whether to split sentences into different Dataset rows.
A flag indicating whether to split sentences into different Dataset rows. Useful for higher parallelism in fat rows. Defaults to false.
Override for additional custom schema checks
Override for additional custom schema checks
Whether to split sentences into different Dataset rows.
Whether to split sentences into different Dataset rows. Useful for higher parallelism in fat rows. Defaults to false.
Get impossible penultimates
input annotations columns currently used
Get model architecture
Gets annotation column name going to generate
Gets annotation column name going to generate
Impossible penultimates
Output annotator type : SENTENCE_EMBEDDINGS
Output annotator type : SENTENCE_EMBEDDINGS
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
Model architecture
Output annotator type : CATEGORY
Output annotator type : CATEGORY
Whether to split sentences into different Dataset rows.
Whether to split sentences into different Dataset rows. Useful for higher parallelism in fat rows. Defaults to false.
Set impossible penultimates
Overrides required annotators column if different than default
Overrides required annotators column if different than default
Set architecture
Overrides annotation column name when transforming
Overrides annotation column name when transforming
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[Row]
requirement for pipeline transformation validation.
requirement for pipeline transformation validation. It is called on fit()
whether to only utilize custom bounds for sentence detection
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.
to be validated
True if all the required types are present, else false