如何避免使用 Matcher 在 SpaCy 中重复提取重叠模式?
How to avoid double-extracting of overlapping patterns in SpaCy with Matcher?
我需要通过 python Spacy Matcher 从 2 个列表中提取项目组合。问题如下:
让我们有 2 个列表:
colors=['red','bright red','black','brown','dark brown']
animals=['fox','bear','hare','squirrel','wolf']
我通过以下代码匹配序列:
first_color=[]
last_color=[]
only_first_color=[]
for color in colors:
if ' ' in color:
first_color.append(color.split(' ')[0])
last_color.append(color.split(' ')[1])
else:
only_first_color.append(color)
matcher = Matcher(nlp.vocab)
pattern1 = [{"TEXT": {"IN": only_first_color}},{"TEXT":{"IN": animals}}]
pattern2 = [{"TEXT": {"IN": first_color}},{"TEXT": {"IN": last_color}},{"TEXT":{"IN": animals}}]
matcher.add("ANIMALS", None, pattern1,pattern2)
doc = nlp('bright red fox met black wolf')
matches = matcher(doc)
for match_id, start, end in matches:
string_id = nlp.vocab.strings[match_id] # Get string representation
span = doc[start:end] # The matched span
print(start, end, span.text)
它给出了输出:
0 3 bright red fox
1 3 red fox
4 6 black wolf
如何只提取 'bright red fox' 和 'black wolf'?我应该更改模式规则还是 post-处理匹配项?
任何想法表示赞赏!
您可以使用 spacy.util.filter_spans
:
Filter a sequence of Span objects and remove duplicates or overlaps.
Useful for creating named entities (where one token can only be part
of one entity) or when merging spans with Retokenizer.merge
. When
spans overlap, the (first) longest span is preferred over shorter
spans.
Python代码:
matches = matcher(doc)
spans = [doc[start:end] for _, start, end in matches]
for span in spacy.util.filter_spans(spans):
print(span.start, span.end, span.text)
输出:
0 3 bright red fox
4 6 black wolf
我需要通过 python Spacy Matcher 从 2 个列表中提取项目组合。问题如下: 让我们有 2 个列表:
colors=['red','bright red','black','brown','dark brown']
animals=['fox','bear','hare','squirrel','wolf']
我通过以下代码匹配序列:
first_color=[]
last_color=[]
only_first_color=[]
for color in colors:
if ' ' in color:
first_color.append(color.split(' ')[0])
last_color.append(color.split(' ')[1])
else:
only_first_color.append(color)
matcher = Matcher(nlp.vocab)
pattern1 = [{"TEXT": {"IN": only_first_color}},{"TEXT":{"IN": animals}}]
pattern2 = [{"TEXT": {"IN": first_color}},{"TEXT": {"IN": last_color}},{"TEXT":{"IN": animals}}]
matcher.add("ANIMALS", None, pattern1,pattern2)
doc = nlp('bright red fox met black wolf')
matches = matcher(doc)
for match_id, start, end in matches:
string_id = nlp.vocab.strings[match_id] # Get string representation
span = doc[start:end] # The matched span
print(start, end, span.text)
它给出了输出:
0 3 bright red fox
1 3 red fox
4 6 black wolf
如何只提取 'bright red fox' 和 'black wolf'?我应该更改模式规则还是 post-处理匹配项?
任何想法表示赞赏!
您可以使用 spacy.util.filter_spans
:
Filter a sequence of Span objects and remove duplicates or overlaps. Useful for creating named entities (where one token can only be part of one entity) or when merging spans with
Retokenizer.merge
. When spans overlap, the (first) longest span is preferred over shorter spans.
Python代码:
matches = matcher(doc)
spans = [doc[start:end] for _, start, end in matches]
for span in spacy.util.filter_spans(spans):
print(span.start, span.end, span.text)
输出:
0 3 bright red fox
4 6 black wolf