load_resources.py
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# -*- coding:utf-8 -*-
import re
import sys
import time
import jsonpickle
from django.core.management.base import BaseCommand, make_option
from multiservice.facade import Multiservice
from multiservice.facade.ttypes import *
from multiservice.types.ttypes import *
from lxml import etree
from thrift.transport import TSocket
from webapp.models import Expression, Segment, Source, \
SourceLink, get_or_create_meaning
PORT = 20000
HOST = 'multiservice.nlp.ipipan.waw.pl'
PROCESS_CHAIN = ['Concraft', 'Spejd', 'Nerf', 'MentionDetector']
EXPR_DELIMITERS = [',']
class Command(BaseCommand):
help = 'Load target resource to Periphraser.'
option_list = BaseCommand.option_list + (
make_option('--path',
action='store',
dest='path',
type='str',
default='',
help='Path to resource xml'),) + (
make_option('--source',
action='store',
dest='source',
type='str',
default='',
help='Resource name'),)
def handle(self, *args, **options):
load_sources_data()
load_resource(options['source'], options['path'])
def load_sources_data():
Source.objects.get_or_create(key='sjp', name='SJP', url='http://sjp.pl/',
description=u'Słownik języka polskiego, ortograficzny, wyrazów obcych i słownik do gier w jednym.')
Source.objects.get_or_create(key='szarada', name='szarada.net', url='http://szarada.net/',
description=u'Internetowy świat krzyżówek')
Source.objects.get_or_create(key='plwn', name=u'Słowosieć', url='http://plwordnet.pwr.wroc.pl/',
description=u'Słowosieć (z ang. wordnet) – to słownik semantyczny, który odzwierciedla system leksykalny języka polskiego.')
Source.objects.get_or_create(key='wikidata', name=u'Wikidane', url='https://www.wikidata.org/',
description=u'Wikidane, w języku angielskim Wikidata – projekt internetowy mający na celu stworzenie wolnej, otwartej, wielojęzycznej bazy różnorodnych danych. Głównym zastosowaniem tej bazy danych jest używanie jej w projektach Wikimedia Foundation, przede wszystkim w Wikipedii.')
def load_resource(name, path):
source = Source.objects.get(key=name)
for _, element in etree.iterparse(path):
if element.tag == 'entry' and descriptions_exists(element):
load_entry(source, element)
def descriptions_exists(entry):
return len(entry.getchildren()) > 1
def load_entry(source, entry):
wikilink = ''
plwn_synset = 0
for desc in entry.getchildren():
if 'wikilink' in desc.attrib and desc.attrib['wikilink']:
wikilink = desc.attrib['wikilink']
if 'synset' in desc.attrib and desc.attrib['synset']:
plwn_synset = int(desc.attrib['synset'])
meaning, _ = get_or_create_meaning(plwn_synset, wikilink)
for desc in entry.getchildren():
if desc_is_label(desc, source):
continue
print desc.text
parse_and_load_expression(source, meaning, desc)
if meaning.expressions.count() < 2:
meaning.delete()
def desc_is_label(desc, source):
if source.key == 'wikidata':
expr = desc.text.lower()
if expr.startswith(u'strona ujednoznaczniająca'):
return True
elif expr.startswith(u'kategoria'):
return True
elif expr.startswith(u'lista projektu'):
return True
elif expr.startswith(u'lista w projekcie'):
return True
return False
def parse_and_load_expression(source, meaning, desc):
transport, client = getThriftTransportAndClient(HOST, PORT)
expression = desc.text
request = createRequest(expression, PROCESS_CHAIN)
try:
token = client.putObjectRequest(request)
status = None
while status not in [RequestStatus.DONE, RequestStatus.FAILED]:
status = client.getRequestStatus(token)
time.sleep(0.1)
if status == RequestStatus.DONE:
result = client.getResultObject(token)
load_expression(source, desc, meaning, result)
else:
print >> sys.stderr, client.getException(token)
sys.exit("Stopped loading data!")
finally:
transport.close()
def getThriftTransportAndClient(host, port):
transport = TSocket.TSocket(host, port)
try:
transport = TTransport.TBufferedTransport(transport)
protocol = TBinaryProtocol.TBinaryProtocol(transport)
client = Multiservice.Client(protocol)
transport.open()
return (transport, client)
except:
transport.close()
raise
def createRequest(text, serviceNames):
ttext = TText(paragraphs=[TParagraph(text=chunk)
for chunk in re.split(r'\n\n+', text)])
chain = [RequestPart(serviceName=name) for name in serviceNames]
request = ObjectRequest(ttext, chain)
return request
def load_expression(source, desc, meaning, result):
jsonStr = jsonpickle.encode(result, unpicklable=False)
jsonObj = jsonpickle.decode(jsonStr)
simpler_exprs = []
detected_mentions = get_detected_mentions(jsonObj)
if detected_mentions:
simpler_exprs = split_expr(jsonObj)
if simpler_exprs:
for expr in simpler_exprs:
save_expression(source=source, desc=desc, meaning=meaning,
nerf_category=expr['category'],
expr_segs=expr['tokens'],
biggest_mention_tokens=expr['tokens'],
head=expr['head'])
else:
main_category, expr_segs, head, biggest_mention_tokens = get_expr_info(jsonObj)
save_expression(source, desc, meaning, main_category,
expr_segs, biggest_mention_tokens, head)
def get_detected_mentions(jsonObj):
mentions = []
for para in jsonObj['paragraphs']:
for sent in para['sentences']:
for mnt in sent['mentions']:
mentions.append(mnt)
return mentions
def split_expr(jsonObj):
mentions = []
for para in jsonObj['paragraphs']:
for sent in para['sentences']:
expr_tokens = []
for tok in sent['tokens']:
if tok['orth'] in EXPR_DELIMITERS:
match = get_matching_mention(sent, expr_tokens)
if match:
tokens, head, category = parse_mention_info(sent, match)
mentions.append({'tokens': tokens,
'head': head,
'category': category})
else:
return []
expr_tokens = []
elif not tok['chosenInterpretation']['ctag'] == 'interp':
expr_tokens.append(tok)
if expr_tokens:
match = get_matching_mention(sent, expr_tokens)
if match:
tokens, head, category = parse_mention_info(sent, match)
mentions.append({'tokens': tokens,
'head': head,
'category': category})
else:
return []
return mentions
def get_matching_mention(sent, tokens_to_match):
tokens_to_match_ids = get_tokens_ids(tokens_to_match)
for mention in sent['mentions']:
tokens, _, _ = parse_mention_info(sent, mention)
tokens_ids = get_tokens_ids(tokens)
if set(tokens_ids) == set(tokens_to_match_ids):
return mention
return None
def get_tokens_ids(tokens):
return [tok['id'] for tok in tokens if not tok['chosenInterpretation']['ctag'] == 'interp']
def get_expr_info(jsonObj):
biggest_mention = None
biggest_mention_tokens = []
main_category = ''
expr_segs = []
head = None
for para in jsonObj['paragraphs']:
for sent in para['sentences']:
expr_segs.extend(sent['tokens'])
for mention in sent['mentions']:
if (biggest_mention == None or
len(mention['childIds']) > len(biggest_mention['childIds'])):
biggest_mention = mention
biggest_mention_tokens, head, category = parse_mention_info(sent, mention)
if category:
main_category = category
return main_category, expr_segs, head, biggest_mention_tokens
def parse_mention_info(sentence, mention):
tokens = []
for token_id in mention['childIds']:
tokens.append((token for token in sentence['tokens'] if token["id"] == token_id).next())
head = (token for token in sentence['tokens'] if token["id"] == mention['headIds'][0]).next()
category = get_category(sentence, head)
return tokens, head, category
def get_category(sentence, mention_head):
for name in sentence['names']:
if mention_head['id'] in name['childIds']:
return name['type']
return ''
def save_expression(source, desc, meaning, nerf_category,
expr_segs, biggest_mention_tokens, head):
expression = get_expr_text(expr_segs)
expression_upper = expression.upper()
categories = []
if desc.attrib['categories']:
categories = desc.attrib['categories'].split(';')
if nerf_category and (len(expr_segs) > 1 or expression[0].isupper()):
categories.append(nerf_category)
meaning.add_domains(categories)
if not meaning.expressions.filter(text=expression_upper, main_expression=None).exists():
exact_link = u''
if 'entrylink' in desc.attrib:
exact_link = desc.attrib['entrylink']
is_catchword = str2boolean(desc.attrib['catchword']) or len(expr_segs) == 1
expr_obj = Expression.objects.create(text=expression_upper, meaning=meaning,
score=0.0, NKJP_freq=0, is_catchword=is_catchword)
add_segments(expr_obj, expr_segs, head)
SourceLink.objects.create(source=source, exact_link=exact_link, expression=expr_obj)
if biggest_mention_tokens and len(expr_segs) != len(biggest_mention_tokens):
mention_text = get_expr_text(biggest_mention_tokens)
mention_text_upper = mention_text.upper()
mention_obj = Expression.objects.create(text=mention_text_upper, meaning=meaning,
main_expression=expr_obj,
score=0.0, NKJP_freq=0, is_catchword=False)
add_segments(mention_obj, biggest_mention_tokens, head)
def get_expr_text(tokens):
expr = ''
for tok in tokens:
if tok['noPrecedingSpace']:
expr += tok['orth']
else:
expr += ' %s' % tok['orth']
return expr.strip()
def str2boolean(bool_str):
if bool_str == 'true':
return True
return False
def add_segments(expr_obj, tokens, head):
position = 1
for seg in tokens:
is_head = False
if seg == head:
is_head = True
Segment.objects.create(position_in_expr=position, expression=expr_obj,
orth=seg['orth'], base=seg['chosenInterpretation']['base'],
ctag=seg['chosenInterpretation']['ctag'],
msd=seg['chosenInterpretation']['msd'], is_head=is_head)
position += 1