これは私のコードです:
def _parse(self, text):
"""
This is the core interaction with the parser.
It returns a Python data-structure, while the parse()
function returns a JSON object
"""
# CoreNLP interactive shell cannot recognize newline
if '\n' in text or '\r' in text:
to_send = re.sub("[\r\n]", " ", text).strip()
else:
to_send = text
self.corenlp.sendline(to_send)
max_expected_time = max(300.0, len(to_send) / 3.0)
# repeated_input = self.corenlp.except("\n") # confirm it
t = self.corenlp.expect(["\nNLP> ", pexpect.TIMEOUT, pexpect.EOF,
"\nWARNING: Parsing of sentence failed, possibly because of out of memory."],
timeout=max_expected_time)
incoming = self.corenlp.before
lag = incoming.split(b"\r\n")
incoming = b"\r\n".join(lag).decode('latin-1').encode('utf-8')
if t == 1:
# TIMEOUT, clean up anything left in buffer
print >>sys.stderr, {'error': "timed out after %f seconds" % max_expected_time,
'input': to_send,
'output': incoming}
raise TimeoutError("Timed out after %d seconds" % max_expected_time)
elif t == 2:
# EOF, probably crash CoreNLP process
print >>sys.stderr, {'error': "CoreNLP terminates abnormally while parsing",
'input': to_send,
'output': incoming}
raise ProcessError("CoreNLP process terminates abnormally while parsing")
elif t == 3:
# out of memory
print >>sys.stderr, {'error': "WARNING: Parsing of sentence failed, possibly because of out of memory.",
'input': to_send,
'output': incoming}
raise OutOfMemoryError
if VERBOSE:
print("%s\n%s" % ('=' * 40, incoming))
try:
results = parse_parser_results(incoming)
except ixception as e:
if VERBOSE:
print(traceback.format_exc())
raise e
self.pre_loaded_analisys_dict[to_send] = results
with open(self.pre_analysis,"w", encoding = 'utf-8') as f:
json.dump(self.pre_loaded_analisys_dict,f)
return results
そして、このエラーが発生しました（多くの用語を解析していますが、そのエラーが発生したのは初めてです）：
>>: 'builtin_function_or_method' および '_io.TextIOWrapper' のオペランド タイプがサポートされていません
何か案は？
編集：printint着信変数私はこれを持っています：
b'Q\r\n注釈パイプラインのタイミング情報:\r\nTokenizerAnnotator: 0.0 秒\r\nWordsToSentencesAnnotator: 0.0 秒\r\nPOSTaggerAnnotator: 0.0 秒\r\nMorphaAnnotator: 0.1 秒\r\nNERCombinerAnnotator: 0.4 秒.\r\n合計: 0.6 秒。606.1 トークン/秒で 337 トークン。\r\nパイプラインのセットアップ: 0.0 秒\r\nStanfordCoreNLP パイプラインの合計時間: 138.7 秒\r\n'
次のようなものを取得する必要がある場合:
b'Contusion of Knee\r\nSentence #1 (3 tokens):\r\nContusion of Knee\r\n[Text=Contusion CharacterOffsetBegin=0 CharacterOffsetEnd=9 PartOfSpeech=NN Lemma=contusion NamedEntityTag=O] [Text=of CharacterOffsetBegin=10 CharacterOffsetEnd=12 PartOfSpeech=IN Lemma=of NamedEntityTag=O] [Text=knee CharacterOffsetBegin=13 CharacterOffsetEnd=17 PartOfSpeech=NN Lemma=knee NamedEntityTag=O] \r'