def answer_question(input_question):
en_doc = nlp(u'' + input_question)
question_class = classify_question(en_doc)
print("Class:", question_class)
question_keywords = extract_features(question_class, en_doc)
print("Question Features:", question_keywords)
question_query = construct_query(question_keywords, en_doc)
print("Question Query:", question_query)
print("Fetching Knowledge source...")
wiki_pages = fetch_wiki(question_keywords, number_of_search=3)
print("Pages Fetched:", len(wiki_pages))
# Anaphora Resolution
ranked_wiki_docs = rank_docs(question_keywords)
print("Ranked Pages:", ranked_wiki_docs)
candidate_answers, split_keywords = get_candidate_answers(
question_query, ranked_wiki_docs, nlp)
print("Candidate Answer:", "(" + str(len(candidate_answers)) + ")",
candidate_answers)
print("Answer:", " ".join(candidate_answers))
answer = " ".join(candidate_answers)
return answer
def answer_question(input_question):
warnings.warn("This method is now deprecated.", DeprecationWarning)
en_nlp = spacy.load('en_core_web_md')
en_doc = en_nlp(u'' + input_question)
question_class = classify_question(en_doc)
print("Class:", question_class)
question_keywords = extract_features(question_class, en_doc)
print("Question Features:", question_keywords)
question_query = construct_query(question_keywords, en_doc)
print("Question Query:", question_query)
print("Fetching Knowledge source...")
wiki_pages = fetch_wiki(question_keywords, number_of_search=3)
print("Pages Fetched:", len(wiki_pages))
# Anaphora Resolution
ranked_wiki_docs = rank_docs(question_keywords)
print("Ranked Pages:", ranked_wiki_docs)
candidate_answers, split_keywords = get_candidate_answers(
question_query, ranked_wiki_docs, en_nlp)
print("Candidate Answer:", "(" + str(len(candidate_answers)) + ")",
candidate_answers)
print("Answer:", " ".join(candidate_answers))
answer = " ".join(candidate_answers)
return answer
def answer_question(q, num_sentences):
q = nlp(u'' + q)
question_class = classify_question(q)
_logger.info("Question Class: {}".format(question_class))
question_keywords = extract_features(question_class, q)
_logger.debug("Question Features: {}".format(question_keywords))
query = construct_query(question_keywords, q)
_logger.debug("Query: {}".format(query))
_logger.info("Retrieving {} wikipedia pages...".format(num_sentences))
wiki_pages = fetch_wiki(question_keywords, number_of_search=num_sentences)
_logger.debug("Pages retrieved: {}".format(len(wiki_pages)))
# Anaphora Resolution
ranked_wiki_docs = rank_docs(question_keywords)
_logger.debug("Ranked pages: {}".format(ranked_wiki_docs))
candidate_answers, keywords = get_candidate_answers(query, ranked_wiki_docs, nlp)
_logger.info("Candidate answers ({}):\n{}".format(len(candidate_answers), '\n'.join(candidate_answers)))
return " ".join(candidate_answers)
def process_answer(self):
_logger.info("Retrieving {} Wikipedia pages...".format(
self.search_depth))
search_wikipedia(self.question_keywords, self.search_depth)
# Anaphora Resolution
wiki_pages = search_rank(self.query)
_logger.info("Pages retrieved: {}".format(len(wiki_pages)))
self.candidate_answers, keywords = get_candidate_answers(
self.query, wiki_pages, self.nlp)
_logger.info("Candidate answers ({}):\n{}".format(
len(self.candidate_answers), '\n'.join(self.candidate_answers)))
return " ".join(self.candidate_answers)
def process_answer(self):
_logger.info("Retrieving {} wikipedia pages...".format(
self.search_depth))
wiki_pages = fetch_wiki(self.question_keywords,
number_of_search=self.search_depth)
_logger.debug("Pages retrieved: {}".format(len(wiki_pages)))
# Anaphora Resolution
ranked_wiki_docs = rank_docs(self.question_keywords)
_logger.debug("Ranked pages: {}".format(ranked_wiki_docs))
self.candidate_answers, keywords = get_candidate_answers(
self.query, ranked_wiki_docs, self.nlp)
_logger.info("Candidate answers ({}):\n{}".format(
len(self.candidate_answers), '\n'.join(self.candidate_answers)))
return " ".join(self.candidate_answers)