LF_ApplyChunking Processing Resource

The chunking application PR allows you to apply a chunking classifier you already learned using the chunking training PR. The PR has no init time parameters. Here are the runtime parameters:

• algorithmParameters: At application time, this runtime parameter is a catch-all for various currently undocumented switches that don’t warrant their own parameter. You can leave it blank.
• confidenceThreshold (double, default: empty, do not use): the minimum average (over all instance classifications)
  confidence score threshold required for a chunk to get assigned (this has no effect if the algorithm does not produce a classification confidence score). If the minimum confidence is not reached, no chunk annotation is created.
• dataDirectory: the directory where the trained model is saved
• inputASName: the input annotation set containing instance annotations and attribute annotations
• instanceType: the annotation type to classify; probably Token or equivalent
• outputASName: annotation set where the new chunk annotations are placed (blank/not specified means the default annotation set)
• sequenceSpan: for sequence classifiers only, the sequence span you gave at training time (or equivalent).