allennlp.data.dataset_readers.ontonotes_ner

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

tokens : TextField
The tokens in the sentence.
tags : SequenceLabelField
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_indexers : Dict[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_scheme : str, (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(tokens: typing.List[allennlp.data.tokenizers.token.Token], ner_tags: typing.List[str] = None) → allennlp.data.instance.Instance[source]

We take pre-tokenized input here, because we don’t have a tokenizer in this class.