def __init__(self):
self.kb = sling.Store()
self.kb.lockgc()
self.kb.load("local/data/e/wiki/kb.sling", snapshot=True)
self.instanceof = self.kb['P31']
self.has_part = self.kb['P527']
self.part_of = self.kb['P361']
self.item_category = self.kb['/w/item/category']
self.date_of_birth = self.kb['P569']
self.date_of_death = self.kb['P570']
self.inception = self.kb['P571']
self.dad = self.kb['P576'] # dissolved, abolished or demolished
self.wikimedia_category = self.kb['Q4167836']
self.date_types = [
self.kb['Q29964144'], # year BC
self.kb['Q577'], # year
self.kb['Q39911'], # decade
self.kb['Q578'], # century
self.kb['Q36507'], # millennium
]
self.human = self.kb['Q5']
self.item = self.kb["item"]
self.facts = self.kb["facts"]
self.provenance = self.kb["provenance"]
self.category = self.kb["category"]
self.method = self.kb["method"]
self.calendar = sling.Calendar(self.kb)
self.names = sling.PhraseTable(
self.kb, "local/data/e/wiki/en/phrase-table.repo")
self.kb.freeze()
self.date_type = {}
self.conflicts = 0
def init_phrase_table():
base_path = '../../sling/'
kb = sling.Store()
kb.load(os.path.join(base_path, 'local/data/e/wiki/kb.sling'))
names = sling.PhraseTable(
kb, os.path.join(base_path, 'local/data/e/wiki/en/phrase-table.repo'))
kb.freeze()
return names
def init(self, task):
self.kb = load_kb(task)
self.names = sling.PhraseTable(self.kb,
task.input("phrase-table").name)
self.min_members = int(task.param("min_members"))
self.num_parses_bins = [1, 2, 3, 5, 10, 20, 50, 100, 200]
# Lookup some handles in advance.
self.h_language = self.lookup("/lang/" + task.param("language"))
self.h_lang = self.lookup("lang")
self.main_topic = self.lookup("P301") # present in topical categories
self.h_member = self.lookup("/w/item/member")
self.h_instanceof = self.lookup('P31')
self.h_subclassof = self.lookup('P279')
self.h_category = self.lookup('Q4167836')
self.h_category_contains = self.lookup('P4224')
self.english = task.param("language") == "en"
# The following kinds of categories won't be processed.
self.uninteresting_categories = set([
self.lookup('Q20769287'), # disambiguation category
self.lookup('Q15407973'), # list category
#self.lookup('Q56428020'), # template category
self.lookup('Q23894233'), # stub category
self.lookup('Q24046192'), # admin category
self.lookup('Q15647814'), # user category
self.lookup('Q20010800'), # user language category
self.lookup('Q30432511'), # meta category
self.lookup('Q13331174') # navbox category
])
# These pids will not be considered as resolution for spans.
self.pids_to_ignore = set([
self.h_instanceof, # P31 = instance of
self.lookup('P279'), # P279 = subclass of
self.lookup('P971'), # P971 = category combines topics
self.lookup('P4224'), # P4224 = category contains
])
# These QIDs will not be considered as resolutions for spans.
self.base_qids = set([
self.lookup('Q5'), # human
self.lookup('Q215627'), # person
self.lookup('Q17334923'), # location
self.lookup('Q811430'), # construction
self.lookup('Q43229'), # organization
self.lookup('Q2385804'), # educational institution
self.lookup('Q294163'), # public institution
self.lookup('Q15401930'), # product
self.lookup('Q12737077'), # occupation
self.lookup('Q192581'), # job
self.lookup('Q4164871'), # position
self.lookup('Q216353') # title
])
self.extractor = sling.api.FactExtractor(self.kb)
def __init__(self):
self.kb = sling.Store()
self.kb.lockgc()
self.kb.load("local/data/e/wiki/kb.sling", snapshot=True)
self.instanceof = self.kb['P31']
self.has_part = self.kb['P527']
self.part_of = self.kb['P361']
self.subclass = self.kb['P279']
self.item_category = self.kb['/w/item/category']
self.date_of_birth = self.kb['P569']
self.date_of_death = self.kb['P570']
self.inception = self.kb['P571']
self.dad = self.kb['P576'] # dissolved, abolished or demolished
self.wikimedia_category = self.kb['Q4167836']
self.date_types = [
self.kb['Q29964144'], # year BC
self.kb['Q577'], # year
self.kb['Q39911'], # decade
self.kb['Q578'], # century
self.kb['Q36507'], # millennium
]
self.human = self.kb['Q5']
self.business = self.kb['Q4830453']
self.organization = self.kb['Q43229']
self.item = self.kb["item"]
self.facts = self.kb["facts"]
self.provenance = self.kb["provenance"]
self.category = self.kb["category"]
self.method = self.kb["method"]
self.names = sling.PhraseTable(
self.kb, "local/data/e/wiki/en/phrase-table.repo")
self.kb.freeze()
self.date_type = {}
self.conflicts = 0
self.months = {
"January": 1,
"February": 2,
"March": 3,
"April": 4,
"May": 5,
"June": 6,
"July": 7,
"August": 8,
"September": 9,
"October": 10,
"November": 11,
"December": 12
}
def pruneTriples(triple_file, output_file):
"""
******** This method needs to be called in a python env that has sling!!! *******
Input: 1. name of file with tab sepperated SRO triples
2. name of the output file
Output: file containing triples where both entities have QCodes.
"""
t1 = time.time() # start the clock
base_path = cfg['all']['base_path']
kb = sling.Store()
kb.load(base_path + "local/data/e/wiki/kb.sling")
names = sling.PhraseTable(
kb, base_path + "local/data/e/wiki/en/phrase-table.repo")
kb.freeze()
print("* Sling KB loaded in %0.3fs." % (time.time() - t1))
verified_triples = []
with open(triple_file, "r") as inFile:
tsvreader = csv.reader(inFile, delimiter="\t")
for triple in tsvreader:
entity1 = triple[0]
relation = triple[1]
entity2 = triple[2]
score = triple[3]
hasBoth, qcode1, qcode2 = confirmEntities(names, entity1, entity2)
if (hasBoth):
q_triple = (qcode1, relation, qcode2, score)
verified_triples.append(q_triple)
with open(output_file, "w") as outFile:
writer = csv.writer(outFile, delimiter='\t')
for t in verified_triples:
s = t[0] # subject
r = t[1] # relation
o = t[2] # object
c = t[3] # confidence score
writer.writerow([s, r, o, c])
def __init__(self):
# Initialize commons store with knowledge base.
start = time.time()
self.commons = sling.Store()
self.commons.lockgc()
self.commons.load(wikidir + "/kb.sling", snapshot=True)
self.n_item_member = self.commons['/w/item/member']
self.n_instance_of = self.commons['P31']
self.n_wikimedia_category = self.commons['Q4167836']
self.n_subject = self.commons['subject']
self.extractor = sling.FactExtractor(self.commons)
# Add category subject types.
self.subjects = {}
for subject, item in english_subject_types.iteritems():
self.subjects[subject] = self.commons[item]
# Add properties for subjects.
self.subject_properties = []
for p in subject_properties:
self.subject_properties.append(self.commons[p])
self.commons.freeze()
end = time.time()
print end - start, "secs loading commons"
# Load phrase table.
# TODO(ringgaard): Load language-dependent phrase table.
start = time.time()
self.phrasetab = sling.PhraseTable(self.commons,
wikidir + "/en/phrase-table.repo")
end = time.time()
print end - start, "secs loading phrase table"
# Open category member database.
self.member_db = sling.RecordDatabase(wikidir +
"/wikipedia-members.rec")
# 0: Registration Authority Code
# 1: Country
# 2: Country Code
# 3: Jurisdiction (country or region)
# 4: International name of Register
# 5: Local name of Register
# 6: International name of organisation responsible for the Register
# 7: Local name of organisation responsible for the Register
# 8: Website
# 9: Date IP disclaimer
# 10: Comments
# 11: End Date
kb = sling.Store()
kb.load("data/e/kb/kb.sling")
aliases = sling.PhraseTable(kb, "data/e/kb/en/phrase-table.repo")
def resolve_name(name):
for item in aliases.lookup(name):
return item
return None
reader = csv.reader(open("data/c/lei/2019-12-05_ra-list-v1.5.csv", "r"))
reader.__next__()
for row in reader:
slots = [("registration_authority_code", row[0]), ("country_name", row[1]),
("country_code", row[2]), ("country", resolve_name(row[1]))]
dictionary[key] = dictionary.get(key, 0) + delta
def fact_to_text(fact):
l = []
for f in fact:
l.append(str(f.name))
return ": ".join(l)
commons = sling.Store()
commons.lockgc()
commons.load(wikidir + "/kb.sling", snapshot=True)
n_is = commons["is"]
extractor = sling.FactExtractor(commons)
phrasetab = sling.PhraseTable(commons, wikidir + "/en/phrase-table.repo")
commons.freeze()
class Name:
def __init__(self, doc):
self.doc = doc
self.store = doc.frame.store()
self.covered = [False] * len(doc.tokens)
self.evokes = {}
self.matched = set()
self.skip = []
for t in self.doc.tokens:
self.skip.append(t.word in stop_words)
def overlaps(self, begin, end):
self.elements = [None] * (size * size)
def index(self, i, j):
return i * self.size + j - 1 # second index is 1-based
def assign(self, i, j, span):
self.elements[self.index(i, j)] = span
def get(self, i, j):
return self.elements[self.index(i, j)]
commons = sling.Store()
commons.lockgc()
commons.load("data/e/wiki/kb.sling")
phrasetab = sling.PhraseTable(commons, "data/e/wiki/en/phrase-table.repo")
docschema = sling.DocumentSchema(commons)
factex = sling.FactExtractor(commons)
taxonomy = factex.taxonomy()
titles = [
commons['Q4164871'], # position
commons['Q12737077'], # occupation
commons['Q216353'], # title
]
commons.freeze()
documentids = [
#'Q5945076', 'Q23883660', 'Q43287478', 'Q2147524',
#'Q25048736', 'Q6525874', 'Q3851366', 'Q308735', 'Q2184354',
'Q5337174',
'Q6218080',