com.johnsnowlabs.nlp.annotators
RegexMatcherModel
Related Docs:
object RegexMatcherModel
| package annotators
com.johnsnowlabs.nlp.annotators
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
one-to-many annotation that returns matches as annotations
one-to-many annotation that returns matches as annotations
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
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
rules
Override for additional custom schema checks
Override for additional custom schema checks
Rules represented as Array of Tuples
input annotations columns currently used
Gets annotation column name going to generate
Gets annotation column name going to generate
Can be any of MATCH_FIRST|MATCH_ALL|MATCH_COMPLETE
Input annotator type: DOCUMENT
Input annotator type: DOCUMENT
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
Input annotator type: CHUNK
Input annotator type: CHUNK
Path to file containing a set of regex,key pair.
Path to file containing a set of regex,key pair. readAs can be LINE_BY_LINE or SPARK_DATASET. options contain option passed to spark reader if readAs is SPARK_DATASET.
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
Can be any of MATCH_FIRST|MATCH_ALL|MATCH_COMPLETE
MATCH_ALL|MATCH_FIRST|MATCH_COMPLETE
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()
internal element required for storing annotator to disk
internal element required for storing annotator to disk
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
A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.
Required input and expected output annotator types
Instantiated model of the RegexMatcher. For usage and examples see the documentation of the main class.