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* Add sent_starts to GoldParse * Add SentTagger pipeline component Add `SentTagger` pipeline component as a subclass of `Tagger`. * Model reduces default parameters from `Tagger` to be small and fast * Hard-coded set of two labels: * S (1): token at beginning of sentence * I (0): all other sentence positions * Sets `token.sent_start` values * Add sentence segmentation to Scorer Report `sent_p/r/f` for sentence boundaries, which may be provided by various pipeline components. * Add sentence segmentation to CLI evaluate * Add senttagger metrics/scoring to train CLI * Rename SentTagger to SentenceRecognizer * Add SentenceRecognizer to spacy.pipes imports * Add SentenceRecognizer serialization test * Shorten component name to sentrec * Remove duplicates from train CLI output metrics |
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.. | ||
converters | ||
__init__.py | ||
_schemas.py | ||
convert.py | ||
debug_data.py | ||
download.py | ||
evaluate.py | ||
info.py | ||
init_model.py | ||
link.py | ||
package.py | ||
pretrain.py | ||
profile.py | ||
train.py | ||
validate.py |