class LeadOracle():
def __init__(self, rouge_n=1, metric='f'):
self.rouge_n = rouge_n
self.metric = metric
self.summarizer = Summarizer()
def summarize(self,
ref,
articles,
max_len=40,
len_type='words',
in_titles=False,
out_titles=False,
min_sent_tokens=7,
max_sent_tokens=40):
articles = self.summarizer._preprocess(articles)
scored_summaries = []
for a in articles:
selected_sents = []
current_len = 0
sents = a.sents
if in_titles == False or out_titles == False:
sents = [s for s in sents if not s.is_title]
for s in sents:
l = self.summarizer._sent_len(s, len_type)
new_len = current_len + l
if new_len <= max_len:
selected_sents.append(s.text)
current_len = new_len
if new_len > max_len:
break
if len(selected_sents) >= 1:
summary = ' '.join(selected_sents)
rouge_scores = compute_rouge_n(summary,
ref,
self.rouge_n,
tokenize=True)
score = rouge_scores[self.metric]
scored_summaries.append((summary, score))
scored_summaries.sort(key=lambda x: x[1], reverse=True)
summary = scored_summaries[0][0]
return summary
class Oracle():
def __init__(self, rouge_n=1, metric='f', early_stopping=True):
self.rouge_n = rouge_n
self.metric = metric
self.early_stopping = early_stopping
self.summarizer = Summarizer()
def summarize(self,
ref,
articles,
max_len=40,
len_type='words',
in_titles=False,
out_titles=False,
min_sent_tokens=7,
max_sent_tokens=40):
articles = self.summarizer._preprocess(articles)
sents = [s for a in articles for s in a.sents]
sents = self.summarizer._deduplicate(sents)
if in_titles == False or out_titles == False:
sents = [s for s in sents if not s.is_title]
sent_lens = [self.summarizer._sent_len(s, len_type) for s in sents]
current_len = 0
remaining = list(range(len(sents)))
selected = []
scored_selections = []
ref_words = word_tokenize(ref)
while current_len < max_len and len(remaining) > 0:
scored = []
current_summary_words = [
tok for i in selected for tok in sents[i].words
]
for i in remaining:
new_len = current_len + sent_lens[i]
if new_len <= max_len:
try:
summary_words = current_summary_words + sents[i].words
rouge_scores = compute_rouge_n(summary_words,
ref_words,
rouge_n=self.rouge_n,
tokenize=False)
score = rouge_scores[self.metric]
scored.append((i, score))
except:
pass
if len(scored) == 0:
break
scored.sort(key=lambda x: x[1], reverse=True)
best_idx, best_score = scored[0]
scored_selections.append((selected + [best_idx], best_score))
current_len += sent_lens[best_idx]
selected.append(scored[0][0])
remaining.remove(best_idx)
if self.early_stopping == False:
# remove shorter summaries
max_sents = max([len(x[0]) for x in scored_selections])
scored_selections = [
x for x in scored_selections if len(x[0]) < max_sents
]
scored_selections.sort(key=lambda x: x[1], reverse=True)
if len(scored_selections) == 0:
return ''
best_selection = scored_selections[0][0]
summary_sents = [sents[i].text for i in best_selection]
return ' '.join(summary_sents)