Python NLTK中PCFG的生成

我试图从包含解析树的文件中学习PCFG，例如：

grammar = induce_pcfg(S, productions)

productions = []
for item in treebank.items[:2]:
  for tree in treebank.parsed_sents(item):
    productions += tree.productions()

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这是我的相关代码：

def loadData(path):
    with open(path ,'r') as f:
        data = f.read().split('\n')
    return data

def getTreeData(data):
    return map(lambda s: tree.Tree.fromstring(s), data)

# Main script
print("loading data..")
data = loadData('C:\\Users\\Rayyan\\Desktop\\MSc Data\\NLP\\parseTrees.txt')
print("generating trees..")
treeData = getTreeData(data)
print("done!")
print("done!")

此后，我在互联网上尝试了很多东西，例如：

grammar = induce_pcfg(S, productions)

productions = []
for item in treebank.items[:2]:
  for tree in treebank.parsed_sents(item):
    productions += tree.productions()

但在这里，产品始终是内置函数，例如：

grammar = induce_pcfg(S, productions)

productions = []
for item in treebank.items[:2]:
  for tree in treebank.parsed_sents(item):
    productions += tree.productions()

---

在我的例子中，我尝试用

treeData

替换

production

，但不起作用。我遗漏了什么或做错了什么？

从构建树开始：

from nltk import tree
treeData_rules = []

# Extract the CFG rules (productions) for the sentence
for item in treeData:
    for production in item.productions():
    treeData_rules.append(production)
treeData_rules

然后您可以像这样提取概率CFG（PCFG）：

from nltk import induce_pcfg

S = Nonterminal('S')
grammar_PCFG = induce_pcfg(S, treeData_rules)
print(grammar_PCFG)

---

从建造树木开始：

from nltk import tree
treeData_rules = []

# Extract the CFG rules (productions) for the sentence
for item in treeData:
    for production in item.productions():
    treeData_rules.append(production)
treeData_rules

然后您可以像这样提取概率CFG（PCFG）：

from nltk import induce_pcfg

S = Nonterminal('S')
grammar_PCFG = induce_pcfg(S, treeData_rules)
print(grammar_PCFG)

---

谢谢你的解决方案Kate，我看到它有点晚了！希望课程对你来说进展顺利。谢谢你的解决方案Kate，我看到它有点晚了！希望课程对你来说进展顺利。