Python nltk -- Tree « MARK CHANG'S BLOG

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Python nltk -- Tree

今天我們來看看nltk.Tree要怎麼用

先載入模組

>>> from nltk import Tree

1.build syntax tree

舉個例子
Gary plays baseball
此句子的剖析樹(syntax tree)是這樣：

用nltk.Tree來建構tree：

>>> tree=Tree('S',[Tree('NP',['Gary']),
...           Tree('VP',[Tree('VT',['plays']),
...                     Tree('NP',['baseball'])])])
>>> tree.draw()

即可將剖析樹畫出來
若沒安裝 python-tk,你也可以這樣把tree印出

>>> tree.pprint()
'(S (NP Gary) (VP (VT plays) (NP baseball)))'

2. Subtrees ,Nodes and Leaves

再來可以對tree進行操作
例如：取得tree的subtree, node 和leaf

>>> tree[1]
Tree('VP', [Tree('VT', ['plays']), Tree('NP', ['baseball'])])
>>> tree[1].node
'VP'
>>> tree[1,1]
Tree('NP', ['baseball'])
>>> tree[1,1].node
'NP'
>>> tree[1,1,0]
'baseball'
>>> tree.leaves()
['Gary', 'plays', 'baseball']

3. Grammar , Chomsky normal form

我們也可以看看這個tree是由哪些grammar產生的
可以用productions()得出grammar

>>> tree.productions()
[S -> NP VP, NP -> 'Gary', VP -> VT NP, VT -> 'plays', NP -> 'baseball']

再來,我們可以把grammar轉成chomsky normal form(CNF)
（若不清楚CNF是什麼,請查閱"計算理論"的教科書)
首先,看看一個不符合CNF的例子:

>>> tree2= Tree('S', [ Tree('NP', ['Gary']),
...                     Tree('VT', ['play']), 
...                     Tree('NP', ['baeball'])])
>>> tree2.productions()
[S -> NP VT NP, NP -> 'Gary', VT -> 'play', NP -> 'baeball']
>>> tree2.draw()

S -> NP VT NP不符合chomsky normal form
可以用chomsky_normal_form()

>>> tree2.chomsky_normal_form()
>>> tree2.productions()
[S -> NP S|<VT-NP>, NP -> 'Gary', S|<VT-NP> -> VT NP, VT -> 'play', NP -> 'baeball']
>>> tree2.draw()

轉換後產生了一個新的node,S|<VT-NP>,這樣子就符合CNF了

4.Parse tree from string

如果我們現在有一個string如下：

>>> s=r"(S (NP Gary) (VP (VT plays) (NP baseball)))"

要從這個string建立出tree,可用以下方法：

>>> tree3=Tree.parse(s)
>>> tree3.pprint()
'(S (NP Gary) (VP (VT plays) (NP baseball)))'

結語：

March 01, 2014 00:36
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