nltk.parse.bllip module

class nltk.parse.bllip.BllipParser[source]

Bases: ParserI

Interface for parsing with BLLIP Parser. BllipParser objects can be constructed with the BllipParser.from_unified_model_dir class method or manually using the BllipParser constructor.

__init__(parser_model=None, reranker_features=None, reranker_weights=None, parser_options=None, reranker_options=None)[source]

Load a BLLIP Parser model from scratch. You’ll typically want to use the from_unified_model_dir() class method to construct this object.

Parameters:
  • parser_model (str) – Path to parser model directory

  • reranker_features (str) – Path the reranker model’s features file

  • reranker_weights (str) – Path the reranker model’s weights file

  • parser_options (dict(str)) – optional dictionary of parser options, see bllipparser.RerankingParser.RerankingParser.load_parser_options() for more information.

  • reranker_options (dict(str)) – optional dictionary of reranker options, see bllipparser.RerankingParser.RerankingParser.load_reranker_model() for more information.

classmethod from_unified_model_dir(model_dir, parser_options=None, reranker_options=None)[source]

Create a BllipParser object from a unified parsing model directory. Unified parsing model directories are a standardized way of storing BLLIP parser and reranker models together on disk. See bllipparser.RerankingParser.get_unified_model_parameters() for more information about unified model directories.

Returns:

A BllipParser object using the parser and reranker models in the model directory.

Parameters:
  • model_dir (str) – Path to the unified model directory.

  • parser_options (dict(str)) – optional dictionary of parser options, see bllipparser.RerankingParser.RerankingParser.load_parser_options() for more information.

  • reranker_options (dict(str)) – optional dictionary of reranker options, see bllipparser.RerankingParser.RerankingParser.load_reranker_model() for more information.

Return type:

BllipParser

parse(sentence)[source]

Use BLLIP Parser to parse a sentence. Takes a sentence as a list of words; it will be automatically tagged with this BLLIP Parser instance’s tagger.

Returns:

An iterator that generates parse trees for the sentence from most likely to least likely.

Parameters:

sentence (list(str)) – The sentence to be parsed

Return type:

iter(Tree)

tagged_parse(word_and_tag_pairs)[source]

Use BLLIP to parse a sentence. Takes a sentence as a list of (word, tag) tuples; the sentence must have already been tokenized and tagged. BLLIP will attempt to use the tags provided but may use others if it can’t come up with a complete parse subject to those constraints. You may also specify a tag as None to leave a token’s tag unconstrained.

Returns:

An iterator that generates parse trees for the sentence from most likely to least likely.

Parameters:

sentence (list(tuple(str, str))) – Input sentence to parse as (word, tag) pairs

Return type:

iter(Tree)