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python - spacy规则匹配器从匹配的句子中提取值

转载 作者:行者123 更新时间:2023-12-01 06:49:54 25 4
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我在 spacy 中有一个自定义规则匹配,并且我能够匹配文档中的一些句子。我现在想从匹配的句子中提取一些数字。然而,匹配的句子并不总是具有相同的形状和形式。最好的方法是什么?

# case 1:
texts = ["the surface is 31 sq",
"the surface is sq 31"
,"the surface is square meters 31"
,"the surface is 31 square meters"
,"the surface is about 31,2 square"
,"the surface is 31 kilograms"]

pattern = [
{"LOWER": "surface"},
{"LEMMA": "be", "OP": "?"},
{"TEXT" : {"REGEX": "^(?i:sq(?:uare)?|m(?:et(?:er|re)s?)?)$"}, "OP": "+"},
{"IS_ALPHA": True, "OP": "?"},
{"LIKE_NUM": True},
]

pattern_1 = [
{"LOWER": "surface"},
{"LEMMA": "be", "OP": "?"},
{"IS_ALPHA": True, "OP": "?"},
{"LIKE_NUM": True},
{"TEXT" : {"REGEX": "^(?i:sq(?:uare)?|m(?:et(?:er|re)s?)?)$", "OP": "+"}}
]

matcher = Matcher(nlp.vocab)

matcher.add("Surface", None, pattern, pattern_1)

for index, text in enumerate(texts):
print(f"Case {index}")
doc = nlp(text)
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(match_id, string_id, start, end, span.text)

我的输出将是

Case 0
4898162435462687487 Surface 1 5 surface is 31 sq
Case 1
4898162435462687487 Surface 1 5 surface is sq 31
Case 2
4898162435462687487 Surface 1 6 surface is square meters 31
Case 3
4898162435462687487 Surface 1 5 surface is 31 square
Case 4
4898162435462687487 Surface 1 6 surface is about 31,2 square
Case 5

我只想返回数字(平方米)。类似于 [31, 31, 31, 31, 31.2] 而不是全文。在 spacy 中执行此操作的正确方法是什么?

最佳答案

由于每个匹配项都包含一次 LIKE_NUM 实体,因此您只需解析匹配子树并返回此类标记的第一次出现:

value = [token for token in span.subtree if token.like_num][0]

测试:

results = []
for text in texts:
doc = nlp(text)
matches = matcher(doc)
for match_id, start, end in matches:
span = doc[start:end] # The matched span
results.append([token for token in span.subtree if token.like_num][0])

print(results) # => [31, 31, 31, 31, 31,2]

关于python - spacy规则匹配器从匹配的句子中提取值,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/59070106/

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