def hilight_disagreement(test_amrs,
gold_amr,
iter_num,
aligner=default_aligner,
gold_aligned_fh=None):
"""
Input:
gold_amr: gold AMR object
test_amrs: list of AMRs to compare to
Returns list of disagreement graphs for each gold-test AMR pair.
"""
amr_graphs = []
smatchgraphs = []
gold_label = u'b'
gold_amr.rename_node(gold_label)
(gold_inst, gold_rel1, gold_rel2) = gold_amr.get_triples2()
(gold_inst_t, gold_rel1_t,
gold_rel2_t) = smatch_graph.amr2dict(gold_inst, gold_rel1, gold_rel2)
for a in test_amrs:
aligner.set_amrs(a, gold_amr)
test_label = u'a'
a.rename_node(test_label)
(test_inst, test_rel1, test_rel2) = a.get_triples2()
if gold_aligned_fh:
best_match = get_next_gold_alignments(gold_aligned_fh)
best_match_num = -1.0
else:
(best_match, best_match_num) = smatch.get_fh(
test_inst,
test_rel1,
test_rel2,
gold_inst,
gold_rel1,
gold_rel2,
test_label,
gold_label,
node_weight_fn=aligner.node_weight_fn,
edge_weight_fn=aligner.edge_weight_fn,
iter_num=iter_num)
disagreement = SmatchGraph(test_inst, test_rel1, test_rel2, \
gold_inst_t, gold_rel1_t, gold_rel2_t, \
best_match, const_map_fn=aligner.const_map_fn)
amr_graphs.append(
(disagreement.smatch2graph(node_weight_fn=aligner.node_weight_fn,
edge_weight_fn=aligner.edge_weight_fn),
best_match_num))
smatchgraphs.append(disagreement)
return (amr_graphs, smatchgraphs)
def hilight_disagreement(test_amrs,
gold_amr,
iter_num,
aligner=default_aligner,
gold_aligned_fh=None):
"""
Input:
test_amrs: list of AMRs to compare to
gold_amr: gold AMR object
iter_num: Number of random restarts to use in smatch algorithm.
Returns list of disagreement graphs for each gold-test AMR pair.
"""
smatchgraphs = []
gold_label = u'b'
gold_amr.rename_node(gold_label)
(gold_inst, gold_rel1, gold_rel2) = gold_amr.get_triples2()
(gold_inst_t, gold_rel1_t,
gold_rel2_t) = smatch_graph.amr2dict(gold_inst, gold_rel1, gold_rel2)
# TODO Also compute the weight score if we read gold alignments in from file
# TODO This would require me to handle constants when we read from file
for a in test_amrs:
aligner.set_amrs(a, gold_amr)
test_label = u'a'
a.rename_node(test_label)
(test_inst, test_rel1, test_rel2) = a.get_triples2()
if gold_aligned_fh:
best_match = get_next_gold_alignments(gold_aligned_fh)
best_match_num = -1.0
else:
(best_match, best_match_num) = smatch.get_fh(
test_inst,
test_rel1,
test_rel2,
gold_inst,
gold_rel1,
gold_rel2,
test_label,
gold_label,
node_weight_fn=aligner.node_weight_fn,
edge_weight_fn=aligner.edge_weight_fn,
iter_num=iter_num)
disagreement = SmatchGraph(test_inst, test_rel1, test_rel2, \
gold_inst_t, gold_rel1_t, gold_rel2_t, \
best_match, const_map_fn=aligner.const_map_fn)
smatchgraphs.append((disagreement, best_match_num))
return smatchgraphs
def hilight_disagreement(test_amrs, gold_amr, iter_num, aligner=default_aligner, gold_aligned_fh=None):
"""
Input:
gold_amr: gold AMR object
test_amrs: list of AMRs to compare to
Returns list of disagreement graphs for each gold-test AMR pair.
"""
amr_graphs = []
smatchgraphs = []
gold_label=u'b'
gold_amr.rename_node(gold_label)
(gold_inst, gold_rel1, gold_rel2) = gold_amr.get_triples2()
(gold_inst_t, gold_rel1_t, gold_rel2_t) = smatch_graph.amr2dict(gold_inst, gold_rel1, gold_rel2)
for a in test_amrs:
aligner.set_amrs(a, gold_amr)
test_label=u'a'
a.rename_node(test_label)
(test_inst, test_rel1, test_rel2) = a.get_triples2()
if gold_aligned_fh:
best_match = get_next_gold_alignments(gold_aligned_fh)
best_match_num = -1.0
else:
(best_match, best_match_num) = smatch.get_fh(test_inst, test_rel1, test_rel2,
gold_inst, gold_rel1, gold_rel2,
test_label, gold_label,
node_weight_fn=aligner.node_weight_fn, edge_weight_fn=aligner.edge_weight_fn,
iter_num=iter_num)
disagreement = SmatchGraph(test_inst, test_rel1, test_rel2, \
gold_inst_t, gold_rel1_t, gold_rel2_t, \
best_match, const_map_fn=aligner.const_map_fn)
amr_graphs.append((disagreement.smatch2graph(node_weight_fn=aligner.node_weight_fn,
edge_weight_fn=aligner.edge_weight_fn),
best_match_num))
smatchgraphs.append(disagreement)
return (amr_graphs, smatchgraphs)
def hilight_disagreement(test_amrs, gold_amr, iter_num, aligner=default_aligner, gold_aligned_fh=None):
"""
Input:
test_amrs: list of AMRs to compare to
gold_amr: gold AMR object
iter_num: Number of random restarts to use in smatch algorithm.
Returns list of disagreement graphs for each gold-test AMR pair.
"""
smatchgraphs = []
gold_label=u'b'
gold_amr.rename_node(gold_label)
(gold_inst, gold_rel1, gold_rel2) = gold_amr.get_triples2()
(gold_inst_t, gold_rel1_t, gold_rel2_t) = smatch_graph.amr2dict(gold_inst, gold_rel1, gold_rel2)
# TODO Also compute the weight score if we read gold alignments in from file
# TODO This would require me to handle constants when we read from file
for a in test_amrs:
aligner.set_amrs(a, gold_amr)
test_label=u'a'
a.rename_node(test_label)
(test_inst, test_rel1, test_rel2) = a.get_triples2()
if gold_aligned_fh:
best_match = get_next_gold_alignments(gold_aligned_fh)
best_match_num = -1.0
else:
(best_match, best_match_num) = smatch.get_fh(test_inst, test_rel1, test_rel2,
gold_inst, gold_rel1, gold_rel2,
test_label, gold_label,
node_weight_fn=aligner.node_weight_fn, edge_weight_fn=aligner.edge_weight_fn,
iter_num=iter_num)
disagreement = SmatchGraph(test_inst, test_rel1, test_rel2, \
gold_inst_t, gold_rel1_t, gold_rel2_t, \
best_match, const_map_fn=aligner.const_map_fn)
smatchgraphs.append((disagreement, best_match_num))
return smatchgraphs