Question

我正在处理Stanford sentiment classification数据集，我正在尝试理解编码解析三的两个文件 STree.txt 和 SOStr.txt 每句话。

我如何解码例如这个解析三个？

 Effective|but|too-tepid|biopic

 6|6|5|5|7|7|0

README文件说：

SOStr.txt和STree.txt编码解析树的结构。 STree以父指针格式对树进行编码。每一行   对应于datasetSentences.txt文件中的每个句子

是否有将句子转换为此格式的解析器？我如何解码这个解析三？

我用这个python脚本打印上一句的选区树：

 with open( 'parents.txt') as parentsfile,\
  open( 'sents.txt') as toksfile:
       parents=[]
       toks =[]
       const_trees =[]
       for line in parentsfile:
           parents.append(map(int, line.split()))      
       for line in toksfile:
           toks.append(line.strip().split())
       for i in xrange(len(toks)):
           const_trees.append(load_constituency_tree(parents[i], toks[i]))

           #print (const_trees[i].left.word)
           attrs = vars(const_trees[i])
           print ', '.join("%s: %s" % item for item in attrs.items())

           attrs = vars(const_trees[i].right)
           print ', '.join("%s: %s" % item for item in attrs.items())

           attrs = vars(const_trees[i].left)
           print ', '.join("%s: %s" % item for item in attrs.items()) 

           attrs = vars(const_trees[i].right.right)
           print ', '.join("%s: %s" % item for item in attrs.items())

           attrs = vars(const_trees[i].right.left)
           print ', '.join("%s: %s" % item for item in attrs.items())

           attrs = vars(const_trees[i].left.left)
           print ', '.join("%s: %s" % item for item in attrs.items())

           attrs = vars(const_trees[i].left.right)
           print ', '.join("%s: %s" % item for item in attrs.items()) 

           break

我意识到第一句话的树是以下内容：

                              6
                              |
                +-------------+------------+
                |                          |
                5                          4
      +---------+---------+      +---------+---------+
      |                   |      |                   |
  Effective              but  too-tepid            biopic

就像在这个post中所描述的那样，非终端是短语的类型，但是在树的这种表示中这些是索引，可能是短语类型的字典，我的问题是这个字典在哪里？我怎样才能在一系列短语中转换这个int？

我的解决方案： 我不确定这是解决方案，但是我写了这个功能，将 nltk PTree 传递给相应的父指针列表：

# given the array returned by ptree.trepositions('postorder') of the nltk library i.e
# an array of tuple like this:
# [(0, 0), (0,), (1, 0, 0), (1, 0), (1, 1, 0), (1, 1, 1), (1, 1), (1,), ()]
# that describe the structure of a tree where each index of the array is the  index of a node in the tree in a postorder fashion
# return a list of parents for each node i.e [2, 9, 4, 8, 7, 7, 8, 9, 0] where 0 means that is the root.
# the previous array describe the structure for this tree
#             S
#  ___________|___
# |               VP
# |      _________|___
# NP    V             NP
# |     |          ___|____
# I  enjoyed      my     cookie


def make_parents_list(treepositions):
    parents = []
    for i in range(0,len(treepositions)):
        if len(treepositions[i])==0:
            parent = 0
            parents.append(parent)
        if len(treepositions[i])>0:
            parent_s = [j+1 for j in range(0,len(treepositions)) if ((j > i) and (len(treepositions[j]) == (len(treepositions[i])-1))) ]
            #print parent_s[0]
            parents.append(parent_s[0])
    return parents

编码解析树的结构

0 个答案: