class nltk.parse.IncrementalChartParser(grammar, strategy=[<nltk.parse.chart.LeafInitRule object at 0x2b21a94fb150>, <nltk.parse.chart.EmptyPredictRule object at 0x2b21a94fb190>, <nltk.parse.chart.BottomUpPredictCombineRule object at 0x2b21a94fb1d0>, <nltk.parse.earleychart.CompleteFundamentalRule object at 0x2b21a94fb210>], trace=0, trace_chart_width=50, chart_class=<class 'nltk.parse.earleychart.IncrementalChart'>)[source]

An incremental chart parser implementing Jay Earley’s parsing algorithm:

For each index end in [0, 1, ..., N]:
For each edge such that edge.end = end:
If edge is incomplete and is not a part of speech:
Apply PredictorRule to edge
If edge is incomplete and is a part of speech:
Apply ScannerRule to edge
If edge is complete:
Apply CompleterRule to edge
Return any complete parses in the chart


__init__(grammar[, strategy, trace, ...]) Create a new Earley chart parser, that uses grammar to parse texts.
chart_parse(tokens[, trace])
parse(tokens[, tree_class])
parse_all(sent, *args, **kwargs)
parse_one(sent, *args, **kwargs)
rtype:Tree or None
parse_sents(sents, *args, **kwargs) Apply self.parse() to each element of sents.