event_extraction#
This is a notice that this file/python-module, being a sub-component of Virtualitics’ proprietary NLP pipeline, is the property of Virtualitics, and this file should not be redistributed without the permission of Virtualitics, Inc.
- predict_backend.ml.nlp.event_extraction.EventTuple#
alias of
Event
- predict_backend.ml.nlp.event_extraction.check_for_raised_antecedent(verb, doc, verbose=False)#
Check if this clause is a relative clause and if it is and has antecedent: then if there is no subject marked, fill in the subject position with the antecedent, and otherwise if there is no object marked, fill in the object with the antecedent.
- predict_backend.ml.nlp.event_extraction.check_for_raised_subject_via_xcomp(verb, doc, verbose=False)#
Check if this clause is an open clausal complement (marked by an xcomp dependency relation) of the containing clause (if one exists), and if that is the case, and if there is no subject in this clause, then try to fill in the subject for this clause by retrieving the (raised) object (or subject) of the higher clause.
- predict_backend.ml.nlp.event_extraction.extract_and_deconjoin_events(sentence, spacy_nlp, verbose=False)#
- predict_backend.ml.nlp.event_extraction.extract_argument_conjuncts(arg_head, doc)#
- predict_backend.ml.nlp.event_extraction.extract_compound_arg_chain(arg_head)#
- predict_backend.ml.nlp.event_extraction.extract_event_from_clause(verb, doc, verbose=False)#
- predict_backend.ml.nlp.event_extraction.extract_events(sentence, spacy_nlp, verbose=False)#
- predict_backend.ml.nlp.event_extraction.extract_prep_pobj_args(verb_token)#
- predict_backend.ml.nlp.event_extraction.first_arg(xs)#
- predict_backend.ml.nlp.event_extraction.idx2token(idx, doc)#
- predict_backend.ml.nlp.event_extraction.multiply_out_event_arguments(event, doc)#
- predict_backend.ml.nlp.event_extraction.retrieve_agent_nsubj(verb, doc)#
This method identifies an argument of the verb connected via a dependency chain: VERB–agent–>ADP(by)–pobj–>NOUN