ToDo: Review implementation, Current implementation generates spaces between non-words, potentially breaking tokens
ToDo: Review implementation, Current implementation generates spaces between non-words, potentially breaking tokens
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
input annotations columns currently used
Gets annotation column name going to generate
Gets annotation column name going to generate
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
Annotator reference id.
Annotator reference id. Used to identify elements in metadata or to refer to this annotator type
Overrides required annotators column if different than default
Overrides required annotators column if different than default
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()
required internal uid for saving annotator
required internal uid for saving annotator
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
Annotator that cleans out tokens. Requires stems, hence tokens