def __call__(self, s1, context):
s2 = make_stream_item(s1.stream_time.zulu_timestamp, s1.abs_url)
s2.schost = s1.schost
s2.source = s1.source
s2.source_metadata['kba-2012'] = s1.source_metadata
logger.debug('len(original .body.raw) = %d' % len(s1.body.raw))
#logger.critical(repr(s2))
s2.body = ContentItem(
raw=s1.body.raw,
encoding=s1.body.encoding,
## default, might get overwritten below
media_type='text/html',
taggings={
'stanford':
Tagging(
tagger_id='stanford',
raw_tagging=s1.body.ner,
generation_time=make_stream_time('2012-06-01T00:00:00.0Z'),
tagger_config=
'annotators: {tokenize, cleanxml, ssplit, pos, lemma, ner}, properties: pos.maxlen=100',
tagger_version='Stanford CoreNLP ver 1.2.0',
)
})
if self.config['keep_old_cleansed_as_clean_visible']:
s2.body.clean_visible = s1.body.cleansed
if s1.source == 'social':
s2.body.media_type = 'text/plain'
## the separation of content items in the social stream
## was artificial and annoying, so smoosh them together
s2.body.clean_visible = '\n\n'.join(
[s1.title.cleansed, s1.anchor.cleansed, s1.body.cleansed])
changed_body_raw = False
if s1.title and s1.title.raw:
s2.body.raw = s1.title.raw
s2.body.raw += r'\n\n'
changed_body_raw = True
if s1.anchor and s1.anchor.raw:
s2.body.raw += s1.anchor.raw
s2.body.raw += r'\n\n'
changed_body_raw = True
if changed_body_raw:
s2.body.raw += s1.body.raw
if s1.title:
ci = ContentItem(
raw=s1.title.raw,
encoding=s1.title.encoding,
clean_visible=s1.title.cleansed,
)
s2.other_content['title'] = ci
if s1.anchor:
ci = ContentItem(raw=s1.anchor.raw,
encoding=s1.anchor.encoding,
clean_visible=s1.anchor.cleansed)
s2.other_content['anchor'] = ci
return s2
def align_chunk_with_ner(self, ner_xml_path, i_chunk, o_chunk):
''' iterate through ner_xml_path to fuse with i_chunk into o_chunk '''
## prepare to iterate over the input chunk
input_iter = i_chunk.__iter__()
all_ner = xml.dom.minidom.parse(open(ner_xml_path))
## this converts our UTF-8 data into unicode strings, so when
## we want to compute byte offsets or construct tokens, we
## must .encode('utf8')
for ner_dom in all_ner.getElementsByTagName('FILENAME'):
#for stream_id, raw_ner in files(open(ner_xml_path).read().decode('utf8')):
stream_item = input_iter.next()
## get stream_id out of the XML
stream_id = ner_dom.attributes.get('stream_id').value
if stream_item.stream_id is None:
assert not stream_id, 'out of sync: None != %r' % stream_id
logger.critical('si.stream_id is None... ignoring')
continue
assert stream_id and stream_id == stream_item.stream_id, \
'%s != %s' % (stream_id, stream_item.stream_id)
if not stream_item.body:
## the XML better have had an empty clean_visible too...
#assert not ner_dom....something
continue
tagging = Tagging()
tagging.tagger_id = self.tagger_id # pylint: disable=E1101
'''
## get this one file out of its FILENAME tags
tagged_doc_parts = list(files(ner_dom.toxml()))
if not tagged_doc_parts:
continue
tagged_doc = tagged_doc_parts[0][1]
## hack
hope_original = make_clean_visible(tagged_doc, '')
open(ner_xml_path + '-clean', 'wb').write(hope_original.encode('utf-8'))
print ner_xml_path + '-clean'
'''
#tagging.raw_tagging = tagged_doc
tagging.generation_time = streamcorpus.make_stream_time()
stream_item.body.taggings[self.tagger_id] = tagging # pylint: disable=E1101
## could consume lots of memory here by instantiating everything
sentences, relations, attributes = self.get_sentences(ner_dom)
stream_item.body.sentences[self.tagger_id] = sentences # pylint: disable=E1101
stream_item.body.relations[self.tagger_id] = relations # pylint: disable=E1101
stream_item.body.attributes[self.tagger_id] = attributes # pylint: disable=E1101
logger.debug('finished aligning tokens %s' % stream_item.stream_id)
'''
for num, sent in enumerate(sentences):
for tok in sent.tokens:
print '%d\t%d\t%s' % (num, tok.offsets[OffsetType.LINES].first, repr(tok.token))
'''
if 'align_labels_by' in self.config and self.config[
'align_labels_by']:
assert 'aligner_data' in self.config, 'config missing "aligner_data"'
aligner = AlignmentStrategies[self.config['align_labels_by']]
aligner(stream_item, self.config['aligner_data'])
## forcibly collect dereferenced objects
gc.collect()
try:
o_chunk.add(stream_item)
except MemoryError, exc:
msg = traceback.format_exc(exc)
msg += make_memory_info_msg()
logger.critical(msg)
raise PipelineOutOfMemory(msg)
def align_chunk_with_ner(tmp_ner_path, i_chunk, tmp_done_path):
'''
iterate through the i_chunk and tmp_ner_path to generate a new
Chunk with body.ner
'''
o_chunk = Chunk()
input_iter = i_chunk.__iter__()
ner = ''
stream_id = None
all_ner = xml.dom.minidom.parse(open(tmp_ner_path))
for raw_ner in all_ner.getElementsByTagName('FILENAME'):
stream_item = input_iter.next()
## get stream_id out of the XML
stream_id = raw_ner.attributes.get('docid').value
assert stream_id and stream_id == stream_item.stream_id, \
'%s != %s\nner=%r' % (stream_id, stream_item.stream_id, ner)
tagger_id = 'lingpipe'
tagging = Tagging()
tagging.tagger_id = tagger_id
## get this one file out of its FILENAME tags
tagged_doc = list(lingpipe.files(raw_ner.toxml()))[0][1]
tagging.raw_tagging = tagged_doc
tagging.generation_time = streamcorpus.make_stream_time()
stream_item.body.taggings[tagger_id] = tagging
sentences = list(lingpipe.sentences(tagged_doc))
## make JS labels on individual tokens
assert stream_item.ratings[0].mentions, stream_item.stream_id
john_smith_label = Label()
john_smith_label.annotator = stream_item.ratings[0].annotator
john_smith_label.target_id = stream_item.ratings[0].target_id
# first map all corefchains to their words
equiv_ids = collections.defaultdict(lambda: set())
for sent in sentences:
for tok in sent.tokens:
if tok.entity_type is not None:
equiv_ids[tok.equiv_id].add(cleanse(tok.token))
## find all the chains that are John Smith
johnsmiths = set()
for equiv_id, names in equiv_ids.items():
## detect 'smith' in 'smithye'
_names = cleanse(' '.join(names))
if 'john' in _names and 'smith' in _names:
johnsmiths.add(equiv_id)
print len(johnsmiths)
## now apply the label
for sent in sentences:
for tok in sent.tokens:
if tok.equiv_id in johnsmiths:
tok.labels = [john_smith_label]
stream_item.body.sentences[tagger_id] = sentences
o_chunk.add(stream_item)
## put the o_chunk bytes into the specified file
open(tmp_done_path, 'wb').write(str(o_chunk))
## replace this with log.info()
print 'created %s' % tmp_done_path
def align_chunk_with_ner(self, ner_xml_path, i_chunk, o_chunk):
''' iterate through ner_xml_path to fuse with i_chunk into o_chunk '''
## prepare to iterate over the input chunk
input_iter = i_chunk.__iter__()
all_ner = xml.dom.minidom.parse(open(ner_xml_path))
## this converts our UTF-8 data into unicode strings, so when
## we want to compute byte offsets or construct tokens, we
## must .encode('utf8')
for ner_dom in all_ner.getElementsByTagName('FILENAME'):
#for stream_id, raw_ner in files(open(ner_xml_path).read().decode('utf8')):
stream_item = input_iter.next()
## get stream_id out of the XML
stream_id = ner_dom.attributes.get('stream_id').value
if stream_item.stream_id is None:
assert not stream_id, 'out of sync: None != %r' % stream_id
logger.critical('si.stream_id is None... ignoring')
continue
assert stream_id and stream_id == stream_item.stream_id, \
'%s != %s' % (stream_id, stream_item.stream_id)
if not stream_item.body:
## the XML better have had an empty clean_visible too...
#assert not ner_dom....something
continue
tagging = Tagging()
tagging.tagger_id = self.tagger_id # pylint: disable=E1101
'''
## get this one file out of its FILENAME tags
tagged_doc_parts = list(files(ner_dom.toxml()))
if not tagged_doc_parts:
continue
tagged_doc = tagged_doc_parts[0][1]
## hack
hope_original = make_clean_visible(tagged_doc, '')
open(ner_xml_path + '-clean', 'wb').write(hope_original.encode('utf-8'))
print ner_xml_path + '-clean'
'''
#tagging.raw_tagging = tagged_doc
tagging.generation_time = streamcorpus.make_stream_time()
stream_item.body.taggings[self.tagger_id] = tagging # pylint: disable=E1101
## could consume lots of memory here by instantiating everything
sentences, relations, attributes = self.get_sentences(ner_dom)
stream_item.body.sentences[self.tagger_id] = sentences # pylint: disable=E1101
stream_item.body.relations[self.tagger_id] = relations # pylint: disable=E1101
stream_item.body.attributes[self.tagger_id] = attributes # pylint: disable=E1101
logger.debug('finished aligning tokens %s' % stream_item.stream_id)
'''
for num, sent in enumerate(sentences):
for tok in sent.tokens:
print '%d\t%d\t%s' % (num, tok.offsets[OffsetType.LINES].first, repr(tok.token))
'''
if 'align_labels_by' in self.config and self.config['align_labels_by']:
assert 'aligner_data' in self.config, 'config missing "aligner_data"'
aligner = AlignmentStrategies[ self.config['align_labels_by'] ]
aligner( stream_item, self.config['aligner_data'] )
## forcibly collect dereferenced objects
gc.collect()
try:
o_chunk.add(stream_item)
except MemoryError, exc:
msg = traceback.format_exc(exc)
msg += make_memory_info_msg()
logger.critical(msg)
raise PipelineOutOfMemory(msg)
