nltk.parse.FeatureIncrementalChartParser

class nltk.parse.FeatureIncrementalChartParser

Bases: IncrementalChartParser, FeatureChartParser

__init__(grammar, strategy=[<nltk.parse.chart.LeafInitRule object>, <nltk.parse.featurechart.FeatureEmptyPredictRule object>, <nltk.parse.featurechart.FeatureBottomUpPredictCombineRule object>, <nltk.parse.earleychart.FeatureCompleteFundamentalRule object>], trace_chart_width=20, chart_class=<class 'nltk.parse.earleychart.FeatureIncrementalChart'>, **parser_args)

Create a new Earley chart parser, that uses grammar to parse texts.

Parameters

• grammar (CFG) – The grammar used to parse texts.

• trace (int) – The level of tracing that should be used when parsing a text. 0 will generate no tracing output; and higher numbers will produce more verbose tracing output.

• trace_chart_width (int) – The default total width reserved for the chart in trace output. The remainder of each line will be used to display edges.

• chart_class – The class that should be used to create the charts used by this parser.

chart_parse(tokens, trace=None)

Return the final parse Chart from which all possible parse trees can be extracted.

Parameters

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

Return type

Chart

grammar()

Returns

The grammar used by this parser.

parse(tokens, tree_class=<class 'nltk.tree.tree.Tree'>)

Returns

An iterator that generates parse trees for the sentence. When possible this list is sorted from most likely to least likely.

Parameters

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

Return type

iter(Tree)

parse_all(sent, *args, **kwargs)

Return type

list(Tree)

parse_one(sent, *args, **kwargs)

Return type

Tree or None

parse_sents(sents, *args, **kwargs)

Apply self.parse() to each element of sents. :rtype: iter(iter(Tree))