nltk.parse.RandomChartParser

class nltk.parse.RandomChartParser

Bases: BottomUpProbabilisticChartParser

A bottom-up parser for PCFG grammars that tries edges in random order. This sorting order results in a random search strategy.

sort_queue(queue, chart)

Sort the given queue of Edge objects, placing the edge that should be tried first at the beginning of the queue. This method will be called after each Edge is added to the queue.

Parameters

• queue (list(Edge)) – The queue of Edge objects to sort. Each edge in this queue is an edge that could be added to the chart by the fundamental rule; but that has not yet been added.

• chart (Chart) – The chart being used to parse the text. This chart can be used to provide extra information for sorting the queue.

Return type

None

__init__(grammar, beam_size=0, trace=0)

Create a new BottomUpProbabilisticChartParser, that uses grammar to parse texts.

Parameters

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

• beam_size (int) – The maximum length for the parser’s edge queue.

• 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.

grammar()

Returns

The grammar used by this parser.

parse(tokens)

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))

trace(trace=2)

Set the level of tracing output that should be generated when parsing a text.

Parameters

trace (int) – The trace level. A trace level of 0 will generate no tracing output; and higher trace levels will produce more verbose tracing output.

Return type

None