我正在尝试跟随线程(How to extract subjects in a sentence and their respective dependent phrases?)。我还想从文本中提取主题及其依赖项
import spacy
from textpipeliner import PipelineEngine, Context
from textpipeliner.pipes import *
text = 'No Offline Maps! It used to have offline maps but they disappeared. It now has a menu option to watch a video in exchange for maps but it never downloads the map. Makes the app useless to me.'
pipes_structure = [
SequencePipe([
FindTokensPipe("VERB/nsubj/*"),
NamedEntityFilterPipe(),
NamedEntityExtractorPipe()
]),
FindTokensPipe("VERB"),
AnyPipe([
SequencePipe([
FindTokensPipe("VBD/dobj/NNP"),
AggregatePipe([
NamedEntityFilterPipe("GPE"),
NamedEntityFilterPipe("PERSON")
]),
NamedEntityExtractorPipe()
]),
SequencePipe([
FindTokensPipe("VBD/**/*/pobj/NNP"),
AggregatePipe([
NamedEntityFilterPipe("LOC"),
NamedEntityFilterPipe("PERSON")
]),
NamedEntityExtractorPipe()
])
])
]
engine = PipelineEngine(pipes_structure, Context(text), [0, 1, 2])
engine.process()
当我运行上述代码时,它抛出以下错误:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-22-5f5a5c9e8e51> in <module>()
----> 1 engine = PipelineEngine(pipes_structure, Context(text), [0, 1, 2])
2 engine.process()
~/anaconda3/lib/python3.6/site-packages/textpipeliner/context.py in __init__(self, doc)
4 self._current_sent_idx = -1
5 self._paragraph = self._sents[0:9]
----> 6 for s in doc.sents:
7 self._sents.append(s)
8 self.doc = doc
AttributeError: 'str' object has no attribute 'sents'
我不确定我在哪里犯了错误。有人能帮忙纠正这个问题吗
有趣的图书馆
您的上下文需要是不同的对象。错误明确地说明了这一点。检查包官方example:
看起来您正在将字符串作为
text
变量传入此行将第4行替换为
因为这是他们在你引用的帖子中所做的
这样
text
就不是一个字符串,但它是nlp函数输出的任何类型,所以它在第二行到最后一行工作相关问题 更多 >
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