allennlp.data.dataset_readers.ontonotes_ner¶

class allennlp.data.dataset_readers.ontonotes_ner.OntonotesNamedEntityRecognition(token_indexers: Dict[str, allennlp.data.token_indexers.token_indexer.TokenIndexer] = None, domain_identifier: str = None, coding_scheme: str = 'BIO', lazy: bool = False)[source]¶

Bases: allennlp.data.dataset_readers.dataset_reader.DatasetReader

This DatasetReader is designed to read in the English OntoNotes v5.0 data for fine-grained named entity recognition. It returns a dataset of instances with the following fields:

tokensTextField: The tokens in the sentence.
tagsSequenceLabelField: A sequence of BIO tags for the NER classes.

Note that the “/pt/” directory of the Onotonotes dataset representing annotations on the new and old testaments of the Bible are excluded, because they do not contain NER annotations.

Parameters

token_indexersDict[str, TokenIndexer], optional: We similarly use this for both the premise and the hypothesis. See TokenIndexer. Default is {"tokens": SingleIdTokenIndexer()}.
domain_identifier: ``str``, (default = None): A string denoting a sub-domain of the Ontonotes 5.0 dataset to use. If present, only conll files under paths containing this domain identifier will be processed.
coding_schemestr, (default = None).: The coding scheme to use for the NER labels. Valid options are “BIO” or “BIOUL”.

Returns

A Dataset of Instances for Fine-Grained NER.

text_to_instance(self, tokens: List[allennlp.data.tokenizers.token.Token], ner_tags: List[str] = None) → allennlp.data.instance.Instance[source]¶: We take pre-tokenized input here, because we don’t have a tokenizer in this class.