使用不帶NLTK的Python解析詞性標記的樹語料庫

Question

我有如下的語料庫

(TOP END_OF_TEXT_UNIT)

(TOP (S (NP (DT The)
            (NNP Fulton)
            (NNP County)
            (NNP Grand)
            (NNP Jury))
        (VP (VBD said)
            (NP (NNP Friday))
            (SBAR (-NONE- 0)
                  (S (NP (DT an)
                         (NN investigation)
                         (PP (IN of)
                             (NP (NP (NNP Atlanta))
                                 (POS 's)
                                 (JJ recent)
                                 (JJ primary)
                                 (NN election))))
                     (VP (VBD produced)
                         (NP (`` ``)
                             (DT no)
                             (NN evidence)
                             ('' '')
                             (SBAR (IN that)
                                   (S (NP (DT any)
                                          (NNS irregularities))
                                      (VP (VBD took)
                                          (NP (NN place)))))))))))
     (. .))

我需要解析這棵樹並轉換為如下的句子形式

DT The NNP Fulton NNP County NNP Grand NNP Jury VBD said NNP Friday DT
an NN investigation ...

是否有任何算法可以解析上述內容，或者我們需要使用正則表達式來執行此操作，所以我不想使用NLTK軟件包來執行此操作。

Answer 1

Pyparsing使嵌套表達式解析快速進行。

import pyparsing as pp

LPAR, RPAR = map(pp.Suppress, "()")
expr = pp.Forward()
label = pp.Word(pp.alphas.upper()+'-') | "''" | "``" | "."
word = pp.Literal(".") | "''" | "``" | pp.Word(pp.printables, excludeChars="()")

expr <<= LPAR + label + (word | pp.OneOrMore(expr)) + RPAR

sample = """
(TOP (S (NP (DT The)
            (NNP Fulton)
            (NNP County)
            (NNP Grand)
            (NNP Jury))
        (VP (VBD said)
            (NP (NNP Friday))
            (SBAR (-NONE- 0)
                  (S (NP (DT an)
                         (NN investigation)
                         (PP (IN of)
                             (NP (NP (NNP Atlanta))
                                 (POS 's)
                                 (JJ recent)
                                 (JJ primary)
                                 (NN election))))
                     (VP (VBD produced)
                         (NP (`` ``)
                             (DT no)
                             (NN evidence)
                             ('' '')
                             (SBAR (IN that)
                                   (S (NP (DT any)
                                          (NNS irregularities))
                                      (VP (VBD took)
                                          (NP (NN place)))))))))))
     (. .))
"""

result = pp.OneOrMore(expr).parseString(sample)
print(' '.join(result))

打印：

TOP S NP DT The NNP Fulton NNP County NNP Grand NNP Jury VP VBD said NP NNP Friday SBAR -NONE- 0 S NP DT an NN investigation PP IN of NP NP NNP Atlanta POS 's JJ recent JJ primary NN election VP VBD produced NP `` `` DT no NN evidence '' '' SBAR IN that S NP DT any NNS irregularities VP VBD took NP NN place . .

通常，這樣的解析器將使用pp.Group(expr)保留嵌套元素的分組。 但是在您的情況下，由於您最終還是想要一個平面列表，因此我們將其保留在外-pyparsing的默認行為是僅返回匹配字符串的平面列表。