nltk.parse.chart.CachedTopDownPredictRule

class documentation

class CachedTopDownPredictRule(TopDownPredictRule): (source)

Known subclasses: nltk.parse.earleychart.PredictorRule, nltk.parse.featurechart.FeatureTopDownPredictRule

A cached version of TopDownPredictRule. After the first time this rule is applied to an edge with a given end and next, it will not generate any more edges for edges with that end and next.

If chart or grammar are changed, then the cache is flushed.

Method	`__init__`	Undocumented
Method	`apply`	Return a generator that will add edges licensed by this rule and the given edges to the chart, one at a time. Each time the generator is resumed, it will either add a new edge and yield that edge; or return.
Instance Variable	`_done`	Undocumented

Inherited from TopDownPredictRule:

Constant NUM_EDGES Undocumented

Inherited from AbstractChartRule (via TopDownPredictRule):

Method	`__str__`	Undocumented
Method	`apply_everywhere`	Return a generator that will add all edges licensed by this rule, given the edges that are currently in the chart, one at a time. Each time the generator is resumed, it will either add a new edge and yield that edge; or return.

def __init__(self): (source) ¶

Undocumented

def apply(self, chart, grammar, edge): (source) ¶

overrides nltk.parse.chart.TopDownPredictRule.apply

overridden in nltk.parse.featurechart.FeatureTopDownPredictRule

Return a generator that will add edges licensed by this rule and the given edges to the chart, one at a time. Each time the generator is resumed, it will either add a new edge and yield that edge; or return.

Parameters
chart	Undocumented
grammar	Undocumented
edge	Undocumented
*edges:list(EdgeI)	A set of existing edges. The number of edges that should be passed to `apply()` is specified by the `NUM_EDGES` class variable.
Returns
iter(EdgeI)	Undocumented

_done: dict = (source) ¶

Undocumented