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Add application code and models, update README
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# Marco Kuhlmann <[email protected]>
import sys
from score.core import anchor, intersect;
class Measure(object):
def __init__(self, get_items):
self.get_items = get_items
self.g = 0
self.s = 0
self.c = 0
self.n_updates = 0
self.n_matches = 0
def update(self, gold, system, gidentities, sidentities, trace = 0):
g_items = set(self.get_items(gold, gidentities))
s_items = set(self.get_items(system, sidentities))
self.g += len(g_items)
self.s += len(s_items)
self.c += len(g_items & s_items)
self.n_updates += 1
self.n_matches += g_items == s_items
if trace:
return {"g": len(g_items), "s": len(s_items),
"c": len(g_items & s_items), "m": 1 if g_items == s_items else 0};
def p(self):
return self.c / self.s if self.s != 0 else 0.0
def r(self):
return self.c / self.g if self.g != 0 else 0.0
def f(self):
p = self.p()
r = self.r()
return 2 * p * r / (p + r) if p + r != 0 else 0.0
def m(self):
return self.n_matches / self.n_updates if self.n_updates != 0 else 0.0
def report(self):
json = {}
json["g"] = self.g
json["s"] = self.s
json["c"] = self.c
json["p"] = self.p()
json["r"] = self.r()
json["f"] = self.f()
json["m"] = self.m()
return json
# def argument_predicate_dm(label):
# return True
# def argument_predicate_pas(label):
# arguments = set("adj_ARG1 adj_ARG2 adj_MOD coord_ARG1 coord_ARG2 prep_ARG1 prep_ARG2 prep_ARG3 prep_MOD verb_ARG1 verb_ARG2 verb_ARG3 verb_ARG4 verb_MOD".split())
# return label in arguments
# def argument_predicate_psd(label):
# return label.endswith("-arg")
class Scorer(object):
def __init__(self, include_virtual=True):
self.measures = []
self.measures.append(("labeled", Measure(self.get_itemsL)))
self.measures.append(("unlabeled", Measure(self.get_itemsU)))
# self.measureP = Measure(self.get_itemsP)
# self.measureF = Measure(self.get_itemsF)
# self.measureS = Measure(self.get_itemsS)
self.include_virtual = include_virtual
def identify(self, id):
return self.identities[id]
def get_itemsL(self, graph, identities):
result = {(identities[e.src], identities[e.tgt], e.lab) for e in graph.edges}
if self.include_virtual:
for node in graph.nodes:
if node.is_top:
result.add((-1, identities[node.id], None))
return result
def get_itemsU(self, graph, identities):
result = {(identities[e.src], identities[e.tgt]) for e in graph.edges}
if self.include_virtual:
for node in graph.nodes:
if node.is_top:
result.add((-1, identities[node.id]))
return result
# def get_itemsP(self, graph):
# return {(frame[0], frame[2]) for frame in self.get_itemsF(graph)}
# def get_itemsF(self, graph):
# result = set()
# for node in graph.nodes:
# if self.has_scorable_predicate(node):
# arguments = set()
# for edge in node.outgoing_edges:
# if self.argument_predicate(edge.lab):
# arguments.add(edge)
# extract = (node.id, node.sense, tuple(sorted(arguments)))
# result.add(extract)
# return result
# def get_itemsS(self, graph):
# return {(frame[0], frame[1]) for frame in self.get_itemsF(graph)}
# def argument_predicate(self, label):
# return True
# def has_scorable_predicate(self, node):
# return node.pred and node.pos.startswith("V")
# def show_predications(self, g):
# print(g.id)
# report_predications(self.complete_predications(g))
def update(self, g, s, trace):
gidentities = {node.id: tuple(anchor(node)) for node in g.nodes}
sidentities = {node.id: tuple(anchor(node)) for node in s.nodes}
scores = dict();
for key, measure in self.measures:
score = measure.update(g, s, gidentities, sidentities, trace)
if trace: scores[key] = score;
return scores;
def report(self, n, scores = None):
json = {"n": n}
for info, measure in self.measures:
json[info] = measure.report()
if scores is not None: json["scores"] = scores
return json
def evaluate(gold, system, format = "json", trace = 0):
scorer = Scorer(include_virtual=True)
n = 0
scores = dict() if trace else None
for g, s in intersect(gold, system):
score = scorer.update(g, s, trace)
n += 1
if trace: scores[g.id] = score
result = scorer.report(n, scores)
return result