def run_opencyc(input_file, output_file):
"""
Read an .nq file containing OpenCyc data, outputting a file of
ConceptNet edges and a file of mappings between the Semantic Web and
ConceptNet.
"""
out = MsgpackStreamWriter(output_file)
labels = {}
unlabels = defaultdict(set)
seen_external_urls = set()
# Read through the file once, finding all the "preferred labels". We will
# use these as the surface texts for the nodes.
for subj, pred, obj, _graph in parse_nquads(
open(input_file, encoding='utf-8')):
if pred['url'] == RDF_LABEL:
labels[subj['url']] = obj['text']
unlabels[obj['text']].add(subj['url'])
# Read through the file again and extract ConceptNet edges.
for subj, pred, obj, _graph in parse_nquads(
open(input_file, encoding='utf-8')):
rel_name = resource_name(pred['url'])
web_subj = subj.get('url')
web_obj = obj.get('url')
if rel_name == 'subClassOf' and web_obj is not None and web_subj in labels and web_obj in labels:
subj_label = labels[web_subj]
obj_label = labels[web_obj]
if '_' in subj_label or '_' in obj_label:
continue
if subj_label.startswith('xsd:') or obj_label.startswith('xsd:'):
continue
subj_words = set(simple_tokenize(subj_label))
obj_words = set(simple_tokenize(obj_label))
if (subj_words & BLACKLIST_WORDS) or (obj_words & BLACKLIST_WORDS):
continue
if len(subj_words) > 4 or len(obj_words) > 4:
continue
subj_uri = cyc_to_conceptnet_uri(labels, unlabels, web_subj)
obj_uri = cyc_to_conceptnet_uri(labels, unlabels, web_obj)
out.write(
opencyc_edge('/r/IsA', subj_uri, obj_uri, subj_label,
obj_label))
if (subj_uri, web_subj) not in seen_external_urls:
out.write(external_url_edge(subj_uri, web_subj))
seen_external_urls.add((subj_uri, web_subj))
if (obj_uri, web_obj) not in seen_external_urls:
out.write(external_url_edge(obj_uri, web_obj))
seen_external_urls.add((obj_uri, web_obj))
elif rel_name == 'sameAs' and web_subj in labels and web_obj.startswith(
'http://umbel.org/'):
subj_label = labels[web_subj]
subj_uri = standardized_concept_uri('en', subj_label)
if (subj_uri, web_obj) not in seen_external_urls:
out.write(external_url_edge(subj_uri, web_obj))
seen_external_urls.add((subj_uri, web_obj))
out.close()
def run_opencyc(input_file, output_file):
"""
Read an .nq file containing OpenCyc data, outputting a file of
ConceptNet edges and a file of mappings between the Semantic Web and
ConceptNet.
"""
out = MsgpackStreamWriter(output_file)
labels = {}
unlabels = defaultdict(set)
seen_external_urls = set()
# Read through the file once, finding all the "preferred labels". We will
# use these as the surface texts for the nodes.
for subj, pred, obj, _graph in parse_nquads(open(input_file, encoding='utf-8')):
if pred['url'] == RDF_LABEL:
labels[subj['url']] = obj['text']
unlabels[obj['text']].add(subj['url'])
# Read through the file again and extract ConceptNet edges.
for subj, pred, obj, _graph in parse_nquads(open(input_file, encoding='utf-8')):
rel_name = resource_name(pred['url'])
web_subj = subj.get('url')
web_obj = obj.get('url')
if rel_name == 'subClassOf' and web_obj is not None and web_subj in labels and web_obj in labels:
subj_label = labels[web_subj]
obj_label = labels[web_obj]
if '_' in subj_label or '_' in obj_label:
continue
if subj_label.startswith('xsd:') or obj_label.startswith('xsd:'):
continue
subj_words = set(simple_tokenize(subj_label))
obj_words = set(simple_tokenize(obj_label))
if (subj_words & BLACKLIST_WORDS) or (obj_words & BLACKLIST_WORDS):
continue
if len(subj_words) > 4 or len(obj_words) > 4:
continue
subj_uri = cyc_to_conceptnet_uri(labels, unlabels, web_subj)
obj_uri = cyc_to_conceptnet_uri(labels, unlabels, web_obj)
out.write(opencyc_edge('/r/IsA', subj_uri, obj_uri, subj_label, obj_label))
if (subj_uri, web_subj) not in seen_external_urls:
out.write(external_url_edge(subj_uri, web_subj))
seen_external_urls.add((subj_uri, web_subj))
if (obj_uri, web_obj) not in seen_external_urls:
out.write(external_url_edge(obj_uri, web_obj))
seen_external_urls.add((obj_uri, web_obj))
elif rel_name == 'sameAs' and web_subj in labels and web_obj.startswith('http://umbel.org/'):
subj_label = labels[web_subj]
subj_uri = standardized_concept_uri('en', subj_label)
if (subj_uri, web_obj) not in seen_external_urls:
out.write(external_url_edge(subj_uri, web_obj))
seen_external_urls.add((subj_uri, web_obj))
out.close()
def interlanguage_mapping(interlang_path, ok_concepts):
quads = parse_nquads(bz2.open(str(interlang_path), 'rt'))
mapping = {}
for subj, values in itertools.groupby(quads, itemgetter(0)):
subj_url = subj['url']
subj_concept = translate_dbpedia_url(subj_url)
pieces = split_uri(subj_concept)
if len(pieces) >= 6:
sense = pieces[5]
if 'album' in sense or 'film' in sense or 'series' in sense or 'disambiguation' in sense or 'song' in sense or 'album' in sense or 'band' in sense:
continue
if uri_prefix(subj_concept) in ok_concepts:
targets = [subj_url]
for _subj, _pred, obj, _graph in values:
url = obj['url']
if 'www.wikidata.org' in url:
continue
if url.startswith('http://wikidata.dbpedia.org/'):
wikidata_id = resource_name(url)
# Return early when we see a high-numbered Wikidata ID
if int(wikidata_id[1:]) >= 1000000:
return mapping
targets.append(url)
mapping[subj_url] = targets
return mapping
def interlanguage_mapping(interlang_path, ok_concepts):
quads = parse_nquads(bz2.open(str(interlang_path), 'rt'))
mapping = {}
for subj, values in itertools.groupby(quads, itemgetter(0)):
subj_url = subj['url']
subj_concept = translate_dbpedia_url(subj_url)
pieces = split_uri(subj_concept)
if len(pieces) >= 6:
sense = pieces[5]
if 'album' in sense or 'film' in sense or 'series' in sense or 'disambiguation' in sense or 'song' in sense or 'album' in sense or 'band' in sense:
continue
if uri_prefix(subj_concept) in ok_concepts:
targets = [subj_url]
for _subj, _pred, obj, _graph in values:
url = obj['url']
if 'www.wikidata.org' in url:
continue
if url.startswith('http://wikidata.dbpedia.org/'):
wikidata_id = resource_name(url)
# Return early when we see a high-numbered Wikidata ID
if int(wikidata_id[1:]) >= 1000000:
return mapping
targets.append(url)
mapping[subj_url] = targets
return mapping
def run_wordnet(input_file, output_file):
out = MsgpackStreamWriter(output_file)
synset_senses = defaultdict(list)
sense_synsets = {}
synset_labels = defaultdict(list)
synset_canonical_labels = {}
synset_categories = {}
synset_domains = {}
synset_glosses = {}
synset_disambig = {}
synset_uris = {}
# First pass: find data about synsets
quads = parse_nquads(open(input_file, encoding='utf-8'))
for subj_dict, rel_dict, obj_dict, _graph in quads:
if 'url' not in subj_dict or 'url' not in rel_dict:
continue
subj = subj_dict['url']
rel = rel_dict['url']
obj = obj_dict.get('url')
objtext = obj_dict.get('text')
relname = resource_name(rel)
if relname == 'label':
if obj_dict['lang'] == 'en':
synset_labels[subj].append(objtext)
elif relname == 'sameAs':
if obj.startswith(WN20_URL):
# If we have a link to RDF WordNet 2.0, the URL (URI? IRI?)
# will contain a standardized label for this concept, which
# we should use when we want to use this synset as the name of
# a disambiguation category. RDF WordNet 3.1 assigns synsets
# a number of labels in no particular order, making it hard to
# determine from 3.1 alone what to name a category.
objname = resource_name(obj)
parts = objname.split('-')[1:-2]
# Handle missing apostrophes
label = '-'.join(parts).replace('_s_', "'s_").replace('_s-', "'s_").replace("s__", "s'_").replace("s_-", "s'-").replace('_', ' ')
synset_canonical_labels[subj] = label
elif relname == 'domain_category':
synset_categories[subj] = obj
elif relname == 'lexical_domain':
target = resource_name(obj)
if '.' in target:
domain = target.split('.')[1]
synset_domains[subj] = domain
elif relname == 'gloss':
synset_glosses[subj] = objtext
elif relname == 'reference':
lemma = resource_name(subj)
synset = obj
synset_senses[synset].append(lemma)
sense_synsets[lemma] = synset
used_labels = set(synset_canonical_labels.values())
for synset, values in synset_labels.items():
values.sort(key=lambda label: (label in used_labels,) + label_sort_key(label))
if (
synset not in synset_canonical_labels or
synset_canonical_labels[synset][0].isupper() and synset_domains.get(synset) == 'person'
):
label = values[0]
synset_canonical_labels[synset] = label
used_labels.add(label)
for synset, labels in synset_labels.items():
if synset in synset_categories:
category_name = synset_canonical_labels[synset_categories[synset]]
else:
category_name = synset_domains.get(synset, None)
synset_no_fragment = synset.split('#')[0]
pos = synset_no_fragment[-1].lower()
assert pos in 'nvarsp', synset
if pos == 's':
pos = 'a'
elif pos == 'p':
pos = '-'
if category_name in ('pert', 'all', 'tops'):
category_name = None
synset_disambig[synset] = (pos, category_name)
canon = synset_canonical_labels[synset]
canon_uri = standardized_concept_uri('en', canon, pos, 'wn', category_name)
synset_uris[synset] = canon_uri
for label in labels:
if label != canon:
other_uri = standardized_concept_uri('en', label, pos, 'wn', category_name)
rel_uri = '/r/Synonym'
surface = '[[{0}]] is a synonym of [[{1}]]'.format(label, canon)
edge = make_edge(
rel_uri, other_uri, canon_uri, dataset=DATASET, surfaceText=surface,
license=Licenses.cc_attribution, sources=[SOURCE], weight=2.0
)
out.write(edge)
quads = parse_nquads(open(input_file, encoding='utf-8'))
for subj_dict, rel_dict, obj_dict, _graph in quads:
if 'url' not in subj_dict or 'url' not in rel_dict:
continue
subj = subj_dict['url']
rel = rel_dict['url']
obj = obj_dict.get('url')
relname = resource_name(rel)
if relname in REL_MAPPING:
rel, frame = REL_MAPPING[relname]
reversed_frame = False
if rel.startswith('~'):
rel = rel[1:]
reversed_frame = True
rel_uri = '/r/' + rel
if obj is not None:
obj_uri = synset_uris.get(obj)
if obj not in synset_canonical_labels:
continue
obj_label = synset_canonical_labels[obj]
else:
text = obj_dict['text']
# Some WordNets use strings with "!" in them to indicate
# out-of-band information, such as a missing translation
if (not text) or '!' in text:
continue
lang = obj_dict['lang']
pos, sense = synset_disambig.get(subj, (None, None))
obj_uri = standardized_concept_uri(lang, text, pos, 'wn', sense)
obj_label = text
if subj not in synset_uris or subj not in synset_canonical_labels:
continue
subj_uri = synset_uris[subj]
subj_label = synset_canonical_labels[subj]
license = Licenses.cc_attribution
langcode = subj_uri.split('/')[2]
if langcode in SHAREALIKE_LANGUAGES:
license = Licenses.cc_sharealike
if reversed_frame:
subj_uri, obj_uri = obj_uri, subj_uri
subj_label, obj_label = obj_label, subj_label
surface = frame.format('[[%s]]' % subj_label, '[[%s]]' % obj_label)
edge = make_edge(
rel_uri, subj_uri, obj_uri, dataset=DATASET, surfaceText=surface,
license=license, sources=[SOURCE], weight=2.0
)
out.write(edge)
for wn_url in sorted(synset_uris):
cn_uri = synset_uris[wn_url]
edge = make_edge(
'/r/ExternalURL', cn_uri, wn_url, dataset=DATASET,
license=Licenses.cc_sharealike, sources=[SOURCE], weight=1.0
)
out.write(edge)
out.close()
def run_wordnet(input_file, output_file):
out = MsgpackStreamWriter(output_file)
synset_senses = defaultdict(list)
sense_synsets = {}
synset_labels = defaultdict(list)
synset_canonical_labels = {}
synset_categories = {}
synset_domains = {}
synset_glosses = {}
synset_disambig = {}
synset_uris = {}
# First pass: find data about synsets
quads = parse_nquads(open(input_file, encoding='utf-8'))
for subj_dict, rel_dict, obj_dict, _graph in quads:
if 'url' not in subj_dict or 'url' not in rel_dict:
continue
subj = subj_dict['url']
rel = rel_dict['url']
obj = obj_dict.get('url')
objtext = obj_dict.get('text')
relname = resource_name(rel)
if relname == 'label':
if obj_dict['lang'] == 'en':
synset_labels[subj].append(objtext)
elif relname == 'sameAs':
if obj.startswith(WN20_URL):
# If we have a link to RDF WordNet 2.0, the URL (URI? IRI?)
# will contain a standardized label for this concept, which
# we should use when we want to use this synset as the name of
# a disambiguation category. RDF WordNet 3.1 assigns synsets
# a number of labels in no particular order, making it hard to
# determine from 3.1 alone what to name a category.
objname = resource_name(obj)
parts = objname.split('-')[1:-2]
# Handle missing apostrophes
label = '-'.join(parts).replace('_s_', "'s_").replace(
'_s-',
"'s_").replace("s__",
"s'_").replace("s_-",
"s'-").replace('_', ' ')
synset_canonical_labels[subj] = label
elif relname == 'domain_category':
synset_categories[subj] = obj
elif relname == 'lexical_domain':
target = resource_name(obj)
if '.' in target:
domain = target.split('.')[1]
synset_domains[subj] = domain
elif relname == 'gloss':
synset_glosses[subj] = objtext
elif relname == 'reference':
lemma = resource_name(subj)
synset = obj
synset_senses[synset].append(lemma)
sense_synsets[lemma] = synset
used_labels = set(synset_canonical_labels.values())
for synset, values in synset_labels.items():
values.sort(
key=lambda label: (label in used_labels, ) + label_sort_key(label))
if (synset not in synset_canonical_labels
or synset_canonical_labels[synset][0].isupper()
and synset_domains.get(synset) == 'person'):
label = values[0]
synset_canonical_labels[synset] = label
used_labels.add(label)
for synset, labels in synset_labels.items():
if synset in synset_categories:
category_name = synset_canonical_labels[synset_categories[synset]]
else:
category_name = synset_domains.get(synset, None)
synset_no_fragment = synset.split('#')[0]
pos = synset_no_fragment[-1].lower()
assert pos in 'nvarsp', synset
if pos == 's':
pos = 'a'
elif pos == 'p':
pos = '-'
if category_name in ('pert', 'all', 'tops'):
category_name = None
synset_disambig[synset] = (pos, category_name)
canon = synset_canonical_labels[synset]
canon_uri = standardized_concept_uri('en', canon, pos, 'wn',
category_name)
synset_uris[synset] = canon_uri
for label in labels:
if label != canon:
other_uri = standardized_concept_uri('en', label, pos, 'wn',
category_name)
rel_uri = '/r/Synonym'
surface = '[[{0}]] is a synonym of [[{1}]]'.format(
label, canon)
edge = make_edge(rel_uri,
other_uri,
canon_uri,
dataset=DATASET,
surfaceText=surface,
license=Licenses.cc_attribution,
sources=[SOURCE],
weight=2.0)
out.write(edge)
quads = parse_nquads(open(input_file, encoding='utf-8'))
for subj_dict, rel_dict, obj_dict, _graph in quads:
if 'url' not in subj_dict or 'url' not in rel_dict:
continue
subj = subj_dict['url']
rel = rel_dict['url']
obj = obj_dict.get('url')
relname = resource_name(rel)
if relname in REL_MAPPING:
pos, sense = synset_disambig.get(subj, (None, None))
if relname == 'hypernym' and pos == 'v':
relname = 'hypernym-v'
rel, frame = REL_MAPPING[relname]
reversed_frame = False
if rel.startswith('~'):
rel = rel[1:]
reversed_frame = True
rel_uri = '/r/' + rel
if obj is not None:
obj_uri = synset_uris.get(obj)
if obj not in synset_canonical_labels:
continue
obj_label = synset_canonical_labels[obj]
else:
text = obj_dict['text']
# Some WordNets use strings with "!" in them to indicate
# out-of-band information, such as a missing translation
if (not text) or '!' in text:
continue
lang = obj_dict['lang']
obj_uri = standardized_concept_uri(lang, text, pos, 'wn',
sense)
obj_label = text
if subj not in synset_uris or subj not in synset_canonical_labels:
continue
subj_uri = synset_uris[subj]
subj_label = synset_canonical_labels[subj]
license = Licenses.cc_attribution
langcode = subj_uri.split('/')[2]
if langcode in SHAREALIKE_LANGUAGES:
license = Licenses.cc_sharealike
if reversed_frame:
subj_uri, obj_uri = obj_uri, subj_uri
subj_label, obj_label = obj_label, subj_label
surface = frame.format('[[%s]]' % subj_label, '[[%s]]' % obj_label)
edge = make_edge(rel_uri,
subj_uri,
obj_uri,
dataset=DATASET,
surfaceText=surface,
license=license,
sources=[SOURCE],
weight=2.0)
out.write(edge)
for wn_url in sorted(synset_uris):
cn_uri = synset_uris[wn_url]
edge = make_edge('/r/ExternalURL',
cn_uri,
wn_url,
dataset=DATASET,
license=Licenses.cc_sharealike,
sources=[SOURCE],
weight=1.0)
out.write(edge)
out.close()
def process_dbpedia(input_dir, output_file, concept_file):
"""
Read through multiple DBPedia files and output filtered assertions to
`output_file`.
"""
ok_concepts = read_concept_file(concept_file)
input_path = pathlib.Path(input_dir)
interlang_path = input_path / 'interlanguage_links_en.tql.bz2'
mapped_urls = interlanguage_mapping(interlang_path, ok_concepts)
out = MsgpackStreamWriter(output_file)
types_path = input_path / 'instance_types_en.tql.bz2'
quads = parse_nquads(bz2.open(str(types_path), 'rt'))
for subj, pred, obj, _graph in quads:
subj_url = subj['url']
if (
'Category:' in subj_url or 'File:' in subj_url or
'List_of' in subj_url or '__' in subj_url or
'Template:' in subj_url
):
continue
if subj_url in mapped_urls:
subj_concept = translate_dbpedia_url(subj_url)
obj_type = un_camel_case(resource_name(obj['url']))
if obj_type not in TYPE_BLACKLIST:
obj_concept = standardized_concept_uri('en', obj_type, 'n')
if obj_concept not in CONCEPT_BLACKLIST:
edge = make_edge(
'/r/IsA', subj_concept, obj_concept,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{'contributor': '/s/resource/dbpedia/2015/en'}],
weight=0.5,
surfaceStart=url_to_label(subj['url']),
surfaceEnd=url_to_label(obj['url'])
)
out.write(edge)
for other_url in mapped_urls[subj_url]:
if other_url.startswith('http://wikidata.dbpedia.org/'):
urledge = make_edge(
'/r/ExternalURL',
subj_concept, other_url,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{'contributor': '/s/resource/dbpedia/2015/en'}],
weight=1.0
)
out.write(urledge)
else:
other_concept = translate_dbpedia_url(other_url)
if other_concept:
urledge = make_edge(
'/r/ExternalURL',
other_concept, other_url,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{'contributor': '/s/resource/dbpedia/2015/en'}],
weight=1.0
)
out.write(urledge)
edge = make_edge(
'/r/Synonym',
other_concept, subj_concept,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{'contributor': '/s/resource/dbpedia/2015/en'}],
weight=0.5,
surfaceStart=url_to_label(other_url),
surfaceEnd=url_to_label(subj_url)
)
out.write(edge)
relations_path = input_path / 'mappingbased_objects_en.tql.bz2'
quads = parse_nquads(bz2.open(str(relations_path), 'rt'))
for subj, pred, obj, _graph in quads:
subj_concept = translate_dbpedia_url(subj['url'])
obj_concept = translate_dbpedia_url(obj['url'])
rel_name = resource_name(pred['url'])
if (
subj_concept and obj_concept and
subj['url'] in mapped_urls and obj['url'] in mapped_urls
):
if rel_name in RELATIONS:
rel = RELATIONS[rel_name]
edge = make_edge(
rel, subj_concept, obj_concept,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{'contributor': '/s/resource/dbpedia/2015/en'}],
weight=0.5,
surfaceStart=url_to_label(subj['url']),
surfaceEnd=url_to_label(obj['url'])
)
out.write(edge)
out.close()
def run_wordnet(input_file, output_file):
out = MsgpackStreamWriter(output_file)
synset_senses = defaultdict(list)
sense_synsets = {}
synset_labels = defaultdict(list)
synset_canonical_labels = {}
synset_categories = {}
synset_domains = {}
synset_glosses = {}
synset_disambig = {}
synset_uris = {}
# First pass: find data about synsets
quads = parse_nquads(open(input_file, encoding="utf-8"))
for subj_dict, rel_dict, obj_dict, _graph in quads:
if "url" not in subj_dict or "url" not in rel_dict:
continue
subj = subj_dict["url"]
rel = rel_dict["url"]
obj = obj_dict.get("url")
objtext = obj_dict.get("text")
relname = resource_name(rel)
if relname == "label":
if obj_dict["lang"] == "en":
synset_labels[subj].append(objtext)
elif relname == "sameAs":
if obj.startswith(WN20_URL):
# If we have a link to RDF WordNet 2.0, the URL (URI? IRI?)
# will contain a standardized label for this concept, which
# we should use when we want to use this synset as the name of
# a disambiguation category. RDF WordNet 3.1 assigns synsets
# a number of labels in no particular order, making it hard to
# determine from 3.1 alone what to name a category.
objname = resource_name(obj)
parts = objname.split("-")[1:-2]
# Handle missing apostrophes
label = (
"-".join(parts)
.replace("_s_", "'s_")
.replace("_s-", "'s_")
.replace("s__", "s'_")
.replace("s_-", "s'-")
.replace("_", " ")
)
synset_canonical_labels[subj] = label
elif relname == "domain_category":
synset_categories[subj] = obj
elif relname == "lexical_domain":
target = resource_name(obj)
if "." in target:
domain = target.split(".")[1]
synset_domains[subj] = domain
elif relname == "gloss":
synset_glosses[subj] = objtext
elif relname == "reference":
lemma = resource_name(subj)
synset = obj
synset_senses[synset].append(lemma)
sense_synsets[lemma] = synset
used_labels = set(synset_canonical_labels.values())
for synset, values in synset_labels.items():
values.sort(key=lambda label: (label in used_labels,) + label_sort_key(label))
if (
synset not in synset_canonical_labels
or synset_canonical_labels[synset][0].isupper()
and synset_domains.get(synset) == "person"
):
label = values[0]
synset_canonical_labels[synset] = label
used_labels.add(label)
for synset, labels in synset_labels.items():
if synset in synset_categories:
category_name = synset_canonical_labels[synset_categories[synset]]
else:
category_name = synset_domains.get(synset, None)
synset_no_fragment = synset.split("#")[0]
pos = synset_no_fragment[-1].lower()
assert pos in "nvarsp", synset
if pos == "s":
pos = "a"
elif pos == "p":
pos = "-"
if category_name in ("pert", "all", "tops"):
category_name = None
synset_disambig[synset] = (pos, category_name)
canon = synset_canonical_labels[synset]
canon_uri = standardized_concept_uri("en", canon, pos, "wn", category_name)
synset_uris[synset] = canon_uri
for label in labels:
if label != canon:
other_uri = standardized_concept_uri(
"en", label, pos, "wn", category_name
)
rel_uri = "/r/Synonym"
surface = "[[{0}]] is a synonym of [[{1}]]".format(label, canon)
edge = make_edge(
rel_uri,
other_uri,
canon_uri,
dataset=DATASET,
surfaceText=surface,
license=Licenses.cc_attribution,
sources=[SOURCE],
weight=2.0,
)
out.write(edge)
quads = parse_nquads(open(input_file, encoding="utf-8"))
for subj_dict, rel_dict, obj_dict, _graph in quads:
if "url" not in subj_dict or "url" not in rel_dict:
continue
subj = subj_dict["url"]
rel = rel_dict["url"]
obj = obj_dict.get("url")
relname = resource_name(rel)
if relname in REL_MAPPING:
pos, sense = synset_disambig.get(subj, (None, None))
if relname == "hypernym" and pos == "v":
relname = "hypernym-v"
rel, frame = REL_MAPPING[relname]
reversed_frame = False
if rel.startswith("~"):
rel = rel[1:]
reversed_frame = True
rel_uri = "/r/" + rel
if obj is not None:
obj_uri = synset_uris.get(obj)
if obj not in synset_canonical_labels:
continue
obj_label = synset_canonical_labels[obj]
else:
text = obj_dict["text"]
# Some WordNets use strings with "!" in them to indicate
# out-of-band information, such as a missing translation
if (not text) or "!" in text:
continue
lang = obj_dict["lang"]
obj_uri = standardized_concept_uri(lang, text, pos, "wn", sense)
obj_label = text
if subj not in synset_uris or subj not in synset_canonical_labels:
continue
subj_uri = synset_uris[subj]
subj_label = synset_canonical_labels[subj]
license = Licenses.cc_attribution
langcode = subj_uri.split("/")[2]
if langcode in SHAREALIKE_LANGUAGES:
license = Licenses.cc_sharealike
if reversed_frame:
subj_uri, obj_uri = obj_uri, subj_uri
subj_label, obj_label = obj_label, subj_label
surface = frame.format("[[%s]]" % subj_label, "[[%s]]" % obj_label)
edge = make_edge(
rel_uri,
subj_uri,
obj_uri,
dataset=DATASET,
surfaceText=surface,
license=license,
sources=[SOURCE],
weight=2.0,
)
out.write(edge)
for wn_url in sorted(synset_uris):
cn_uri = synset_uris[wn_url]
edge = make_edge(
"/r/ExternalURL",
cn_uri,
wn_url,
dataset=DATASET,
license=Licenses.cc_sharealike,
sources=[SOURCE],
weight=1.0,
)
out.write(edge)
out.close()
def process_dbpedia(input_dir, output_file, concept_file):
"""
Read through multiple DBPedia files and output filtered assertions to
`output_file`.
"""
ok_concepts = read_concept_file(concept_file)
input_path = pathlib.Path(input_dir)
interlang_path = input_path / 'interlanguage_links_en.tql.bz2'
mapped_urls = interlanguage_mapping(interlang_path, ok_concepts)
out = MsgpackStreamWriter(output_file)
types_path = input_path / 'instance_types_en.tql.bz2'
quads = parse_nquads(bz2.open(str(types_path), 'rt'))
for subj, pred, obj, _graph in quads:
subj_url = subj['url']
if ('Category:' in subj_url or 'File:' in subj_url
or 'List_of' in subj_url or '__' in subj_url
or 'Template:' in subj_url):
continue
if subj_url in mapped_urls:
subj_concept = translate_dbpedia_url(subj_url)
obj_type = un_camel_case(resource_name(obj['url']))
if obj_type not in TYPE_BLACKLIST:
obj_concept = standardized_concept_uri('en', obj_type, 'n')
if obj_concept not in CONCEPT_BLACKLIST:
edge = make_edge('/r/IsA',
subj_concept,
obj_concept,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{
'contributor':
'/s/resource/dbpedia/2015/en'
}],
weight=0.5,
surfaceStart=url_to_label(subj['url']),
surfaceEnd=url_to_label(obj['url']))
out.write(edge)
for other_url in mapped_urls[subj_url]:
if other_url.startswith('http://wikidata.dbpedia.org/'):
urledge = make_edge('/r/ExternalURL',
subj_concept,
other_url,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{
'contributor':
'/s/resource/dbpedia/2015/en'
}],
weight=1.0)
out.write(urledge)
else:
other_concept = translate_dbpedia_url(other_url)
if other_concept:
urledge = make_edge(
'/r/ExternalURL',
other_concept,
other_url,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{
'contributor':
'/s/resource/dbpedia/2015/en'
}],
weight=1.0)
out.write(urledge)
edge = make_edge(
'/r/Synonym',
other_concept,
subj_concept,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{
'contributor':
'/s/resource/dbpedia/2015/en'
}],
weight=0.5,
surfaceStart=url_to_label(other_url),
surfaceEnd=url_to_label(subj_url))
out.write(edge)
relations_path = input_path / 'mappingbased_objects_en.tql.bz2'
quads = parse_nquads(bz2.open(str(relations_path), 'rt'))
for subj, pred, obj, _graph in quads:
subj_concept = translate_dbpedia_url(subj['url'])
obj_concept = translate_dbpedia_url(obj['url'])
rel_name = resource_name(pred['url'])
if (subj_concept and obj_concept and subj['url'] in mapped_urls
and obj['url'] in mapped_urls):
if rel_name in RELATIONS:
rel = RELATIONS[rel_name]
edge = make_edge(rel,
subj_concept,
obj_concept,
dataset='/d/dbpedia/en',
license=Licenses.cc_sharealike,
sources=[{
'contributor':
'/s/resource/dbpedia/2015/en'
}],
weight=0.5,
surfaceStart=url_to_label(subj['url']),
surfaceEnd=url_to_label(obj['url']))
out.write(edge)
out.close()