def main():
out_path = 'Dependency.txt'
with open(out_path, "w") as f:
for chunks in load_cabocha_iter():
for chunk in chunks:
if chunk.dst == -1:
continue
src = chunk.normalized_surface()
dst = chunks[chunk.dst].normalized_surface()
f.write(f'{src}\t{dst}\n')
def main():
with open('out3.txt', 'w', encoding='utf8') as f:
for chunks in load_cabocha_iter():
for i, chunk in enumerate(chunks):
# 係り元のチェック
if not chunk.srcs:
continue
# 動詞の基本形
verbs = [
morph.base for morph in chunk.morphs if morph.pos == '動詞'
]
if not verbs:
continue
# 助詞を含む係り元の文節
particle_phrases = [
chunks[src] for src in chunk.srcs[i]
if any(m.pos == '助詞' for m in chunks[src].morphs)
]
if not particle_phrases:
continue
# 「サ変接続名詞 ＋ を」 をチェックしてparticle_phrasesから除く
# print([a.normalized_surface() for a in particle_phrases])
predicate = ''
for phrase in particle_phrases:
for i in range(len(phrase.morphs) - 1):
if phrase.morphs[i].pos1 == 'サ変接続' and phrase.morphs[
i + 1].surface == 'を':
predicate = f'{phrase.morphs[i].surface}を{verbs[0]}'
particle_phrases.remove(phrase)
break
else:
continue
break
else:
continue
# [(助詞, 文節), (助詞, 文節),...]
particles_phrases = []
for phrase in particle_phrases:
for morph in phrase.morphs:
if morph.pos == '助詞':
particles_phrases.append(
(morph.surface, phrase.normalized_surface()))
break
pp = sorted(particles_phrases)
f.write(
f'{predicate}\t{" ".join([p[0] for p in pp])}\t{" ".join([p[1] for p in pp])}\n'
)
def main():
for chunks in load_cabocha_iter(4):
paths = {} # ex) {0: [5], 1: [2, 3, 4, 5], 3: [4, 5], 4: [5]}
for id_, chunk in enumerate(chunks):
if all(m.pos != '名詞' for m in chunk.morphs):
continue
current = chunk
paths[id_] = []
while current.dst != -1:
paths[id_].append(current.dst)
current = chunks[current.dst]
for k, l in combinations(paths.keys(), 2):
print(obtain_path_str(chunks, paths, k, l))
def main():
cnt = 0
for chunks in load_cabocha_iter():
for chunk in chunks:
if chunk.dst == -1:
continue
src = chunk.normalized_surface()
dst = chunks[chunk.dst].normalized_surface()
if not src or not dst:
continue
print(f'{src}\t{dst}')
cnt += 1
if cnt == 20:
return
def main():
out_path = 'Dependency_noun_verb.txt'
with open(out_path, "w") as f:
for chunks in load_cabocha_iter():
for chunk in chunks:
if chunk.dst == -1:
continue
if all(morph.pos != '名詞' for morph in chunk.morphs):
continue
if all(morph.pos != '動詞'
for morph in chunks[chunk.dst].morphs):
continue
src = chunk.normalized_surface()
dst = chunks[chunk.dst].normalized_surface()
f.write(f'{src}\t{dst}\n')
def main():
path = "noun_to_root.txt"
count = 0
with open(path, "w") as f:
for chunks in load_cabocha_iter():
for chunk in chunks:
if chunk.dst == -1:
continue
if all(m.pos != "名詞" for m in chunk.morphs):
continue
f.write(chunk.normalized_surface())
i = chunk.dst
while i != -1:
f.write(" -> " + chunks[i].normalized_surface())
i = chunks[i].dst
f.write("\n")
def main():
for i, chunks in enumerate(load_cabocha_iter()):
if i != 5:
continue
for chunk in chunks:
if chunk.dst == -1:
continue
noun = [morph.surface for morph in chunk.morphs if morph.pos == '名詞']
if not noun:
continue
path = chunk.normalized_surface() # 吾輩は
current = chunk
while current.dst != -1:
current = chunks[current.dst]
path += f' -> {current.normalized_surface()}' # 吾輩は -> 見た
print(path)
def main():
for i, chunks in enumerate(load_cabocha_iter()):
if i != 7:
continue
edges = []
for j, chunk in enumerate(chunks):
if chunk.dst == -1:
continue
src = chunk.normalized_surface()
dst = chunks[chunk.dst].normalized_surface()
if not src or not dst:
continue
edges.append((j, src, chunk.dst, dst))
# グラフの書き出し
graph = gen_graph(edges)
print(graph.to_string())
graph.write('graph.png', format='png', encoding='utf8')
def main():
with open('out2.txt', 'w', encoding='utf8') as f:
for chunks in load_cabocha_iter():
case_patterns = {}
# {id: [動詞の基本形, [(助詞, 文節), (助詞, 文節),...]]}
for chunk in chunks:
if chunk.dst == -1:
continue
particles = [morph.surface for morph in chunk.morphs if morph.pos == '助詞']
verbs = [morph.base for morph in chunks[chunk.dst].morphs if morph.pos == '動詞']
if not particles or not verbs:
continue
if chunk.dst not in case_patterns:
case_patterns[chunk.dst] = [verbs[0], [(particles[0], chunk.normalized_surface())]]
else:
case_patterns[chunk.dst][1].append((particles[0], chunk.normalized_surface()))
for value in case_patterns.values():
frames = sorted(value[1])
# print(f'{value[0]}\t{" ".join([frame[0] for frame in frames])}\t{" ".join([frame[1] for frame in frames])}')
f.write(f'{value[0]}\t{" ".join([frame[0] for frame in frames])}\t{" ".join([frame[1] for frame in frames])}\n')
def main():
path = "case_pattern_2.txt"
with open(path, "w") as f:
for chunks in load_cabocha_iter():
case_patterns = {}
# {id: [動詞の基本形, [助詞, 助詞,...]]}
for chunk in chunks:
if chunk.dst == -1:
continue
particles = [[chunk.morphs[-1].surface, chunk.normalized_surface()]]
verbs = [morph.base for morph in chunks[chunk.dst].morphs if morph.pos == '動詞']
if not particles or not verbs:
continue
if chunk.dst not in case_patterns:
case_patterns[chunk.dst] = [verbs[0], particles]
else:
case_patterns[chunk.dst][1].extend(particles)
for value in case_patterns.values():
value[1].sort(key=lambda x: x[0])
f.write(f'{value[0]}\t{" ".join([l[0] for l in value[1]])}\t{" ".join([l[1] for l in value[1]])}\n')
def main():
for i, chunks in enumerate(load_cabocha_iter()):
if i != 5:
continue
paths = {} # ex) {0: [5], 1: [2, 3, 4, 5], 3: [4, 5], 4: [5]}
for j, chunk in enumerate(chunks):
if chunk.dst == -1:
continue
noun = [
morph.surface for morph in chunk.morphs if morph.pos == '名詞'
]
if not noun:
continue
current = chunk
paths[j] = []
while current.dst != -1:
paths[j].append(current.dst)
current = chunks[current.dst]
print(paths)
for k, l in combinations(paths.keys(), 2):
print(obtain_path_str(chunks, paths, k, l))
def main():
path = "case_pattern.txt"
with open(path, "w") as f:
for chunks in load_cabocha_iter():
case_patterns = {}
# {id: [動詞の基本形, [助詞, 助詞,...]]}
for chunk in chunks:
if chunk.dst == -1:
continue
particles = [chunk.morphs[-1].surface]
# particles = [morph.surface for morph in chunk.morphs if morph.pos == '助詞']
verbs = [
morph.base for morph in chunks[chunk.dst].morphs
if morph.pos == '動詞'
]
if not particles or not verbs:
continue
if chunk.dst not in case_patterns:
case_patterns[chunk.dst] = [verbs[0], particles]
else:
case_patterns[chunk.dst][1].extend(particles)
for value in case_patterns.values():
f.write(f'{value[0]}\t{" ".join(sorted(value[1]))}\n')
