def node_fn(unused_span_begin, unused_span_end, rule, children):
"""Represent nodes as (target string, int count of possible derivations)."""
target_strings = [target_string for target_string, _ in children]
new_target_string = qcfg_rule.apply_target(rule, target_strings)
child_counts = [child_count for _, child_count in children]
count = _aggregate_counts(child_counts)
return (new_target_string, count)
def __init__(self, score_fn, span_begin, span_end, rule, children):
# Get score.
application_score = score_fn(rule, span_begin, span_end)
self.score = application_score
for node in children:
self.score += node.score
# Get target string.
target_string = qcfg_rule.apply_target(
rule, [node.target_string for node in children])
self.target_string = target_string
application = ScoredAnchoredRuleApplication(rule, span_begin, span_end,
application_score)
# List of ScoredAnchoredRuleApplication, which can be used to inspect
# parse tree for a given prediction.
self.applications = [application]
for node in children:
for application in node.applications:
self.applications.append(application)
def node_fn(unused_span_begin, unused_span_end, rule, children):
"""Represent nodes as target strings."""
return qcfg_rule.apply_target(rule, children)
def node_fn(span_begin, span_end, rule, children):
target_string = qcfg_rule.apply_target(
rule, [node.target_string for node in children])
return RuleApplicationNode(rule, children, span_begin, span_end,
target_string)
def _node_fn(unused_span_begin, unused_span_end, rule, children): """Nodes will represent target strings.""" return qcfg_rule.apply_target(rule, children)