解析多個句子用NLTK

Question

MaltParser

已經有許多MaltParser和/或NLTK相關的問題：

• Malt Parser throwing class not found exception
• How to use malt parser in python nltk
• MaltParser Not Working in Python NLTK
• NLTK MaltParser won't parse
• Dependency parser using NLTK and MaltParser
• Dependency Parsing using MaltParser and NLTK
• Parsing with MaltParser engmalt
• Parse raw text with MaltParser in Java

現在，有MaltParser API的NLTK更穩定的版本：https://github.com/nltk/nltk/pull/944但也有問題，當談到同時分析多個句子。

同時解析了一句似乎罰款：

_path_to_maltparser = '/home/alvas/maltparser-1.8/dist/maltparser-1.8/' 
_path_to_model= '/home/alvas/engmalt.linear-1.7.mco'  
>>> mp = MaltParser(path_to_maltparser=_path_to_maltparser, model=_path_to_model) 
>>> sent = 'I shot an elephant in my pajamas'.split() 
>>> sent2 = 'Time flies like banana'.split() 
>>> print(mp.parse_one(sent).tree()) 
(pajamas (shot I) an elephant in my) 

但分析句子的列表不返回DependencyGraph對象：

_path_to_maltparser = '/home/alvas/maltparser-1.8/dist/maltparser-1.8/' 
_path_to_model= '/home/alvas/engmalt.linear-1.7.mco'  
>>> mp = MaltParser(path_to_maltparser=_path_to_maltparser, model=_path_to_model) 
>>> sent = 'I shot an elephant in my pajamas'.split() 
>>> sent2 = 'Time flies like banana'.split() 
>>> print(mp.parse_one(sent).tree()) 
(pajamas (shot I) an elephant in my) 
>>> print(next(mp.parse_sents([sent,sent2]))) 
<listiterator object at 0x7f0a2e4d3d90> 
>>> print(next(next(mp.parse_sents([sent,sent2])))) 
[{u'address': 0, 
    u'ctag': u'TOP', 
    u'deps': [2], 
    u'feats': None, 
    u'lemma': None, 
    u'rel': u'TOP', 
    u'tag': u'TOP', 
    u'word': None}, 
{u'address': 1, 
    u'ctag': u'NN', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 2, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NN', 
    u'word': u'I'}, 
{u'address': 2, 
    u'ctag': u'NN', 
    u'deps': [1, 11], 
    u'feats': u'_', 
    u'head': 0, 
    u'lemma': u'_', 
    u'rel': u'null', 
    u'tag': u'NN', 
    u'word': u'shot'}, 
{u'address': 3, 
    u'ctag': u'AT', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'AT', 
    u'word': u'an'}, 
{u'address': 4, 
    u'ctag': u'NN', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NN', 
    u'word': u'elephant'}, 
{u'address': 5, 
    u'ctag': u'NN', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NN', 
    u'word': u'in'}, 
{u'address': 6, 
    u'ctag': u'NN', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NN', 
    u'word': u'my'}, 
{u'address': 7, 
    u'ctag': u'NNS', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NNS', 
    u'word': u'pajamas'}, 
{u'address': 8, 
    u'ctag': u'NN', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NN', 
    u'word': u'Time'}, 
{u'address': 9, 
    u'ctag': u'NNS', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NNS', 
    u'word': u'flies'}, 
{u'address': 10, 
    u'ctag': u'NN', 
    u'deps': [], 
    u'feats': u'_', 
    u'head': 11, 
    u'lemma': u'_', 
    u'rel': u'nn', 
    u'tag': u'NN', 
    u'word': u'like'}, 
{u'address': 11, 
    u'ctag': u'NN', 
    u'deps': [3, 4, 5, 6, 7, 8, 9, 10], 
    u'feats': u'_', 
    u'head': 2, 
    u'lemma': u'_', 
    u'rel': u'dep', 
    u'tag': u'NN', 
    u'word': u'banana'}] 

這是爲什麼使用parse_sents()不返回一個可迭代的parse_one？

我可以然而，只是偷懶，做：

_path_to_maltparser = '/home/alvas/maltparser-1.8/dist/maltparser-1.8/' 
_path_to_model= '/home/alvas/engmalt.linear-1.7.mco'  
>>> mp = MaltParser(path_to_maltparser=_path_to_maltparser, model=_path_to_model) 
>>> sent1 = 'I shot an elephant in my pajamas'.split() 
>>> sent2 = 'Time flies like banana'.split() 
>>> sentences = [sent1, sent2] 
>>> for sent in sentences: 
>>> ... print(mp.parse_one(sent).tree()) 

但是這不是我要找的解決方案。 我的問題是如何回答爲什麼parse_sent()返回parse_one()的迭代。以及它如何在NLTK代碼中被修復？

---

@NikitaAstrakhantsev回答後，我已經試過了，現在輸出語法樹，但它似乎混淆和分析之前，兩個句子付諸之一。

# Initialize a MaltParser object with a pre-trained model. 
mp = MaltParser(path_to_maltparser=path_to_maltparser, model=path_to_model) 
sent = 'I shot an elephant in my pajamas'.split() 
sent2 = 'Time flies like banana'.split() 
# Parse a single sentence. 
print(mp.parse_one(sent).tree()) 
print(next(next(mp.parse_sents([sent,sent2]))).tree()) 

[出]：

(pajamas (shot I) an elephant in my) 
(shot I (banana an elephant in my pajamas Time flies like)) 

從它似乎是在做一些奇怪的代碼：https://github.com/nltk/nltk/blob/develop/nltk/parse/api.py#L45

爲什麼在NLTK解析器抽象類嗖嗖兩句話成解析之前的一個？我是否錯誤地撥打parse_sents()？如果是這樣，請撥打parse_sents()的正確方法是什麼？

Answer 1

正如我你的代碼樣本中看到的，你不要在這行

>>> print(next(next(mp.parse_sents([sent,sent2])))) 

叫tree()，而你打電話tree()在所有情況下與parse_one()。

否則，我不明白爲什麼它可能發生的理由：ParserIparse_one()方法不MaltParser無效，但這一切僅僅是調用的MaltParserparse_sents()，看到the code。

UPD：The line you're talking about不叫，因爲parse_sents()在MaltParser覆蓋，並直接調用。

我現在唯一的猜測是java lib maltparser無法正確處理包含多個句子的輸入文件（我的意思是this block - 其中運行java）。也許原麥芽解析器已經改變了格式，現在不是'\n\n'。 不幸的是，我不能自己運行此代碼，因爲maltparser.org第二天就關閉了。我檢查輸入文件是否具有預期的格式（句子由雙端線分隔），所以python包裝器不太可能合併句子。