在动词/名词/形容词之间转换单词

Question

我想要一个python库函数，它可以跨语音的不同部分进行翻译/转换。有时它应该输出多个单词（例如，“coder”和“code”都是动词“to code”的名词，一个是主语，另一个是宾语）

# :: String => List of String
print verbify('writer') # => ['write']
print nounize('written') # => ['writer']
print adjectivate('write') # => ['written']

我最关心的是动词和名词，作为一个我想写的笔记程序。i、 我可以写“咖啡因拮抗剂A1”或者“咖啡因是A1拮抗剂”，用一些NLP，它可以发现它们的意思是一样的。（我知道这不容易，而且需要NLP来解析，而不仅仅是标记，但我想创建一个原型）。

类似的问题。。。 Converting adjectives and adverbs to their noun forms （这个答案只源于词根位置，我想在词根之间切换。）

语言学中的转换

Answer 1

这更像是一种启发式方法。我刚刚把它编码成了这种风格。它使用wordnet中派生的相关形式。我已经实现了名词化。我想verbify的工作原理类似。从我的测试来看，效果相当不错：

from nltk.corpus import wordnet as wn

def nounify(verb_word):
    """ Transform a verb to the closest noun: die -> death """
    verb_synsets = wn.synsets(verb_word, pos="v")

    # Word not found
    if not verb_synsets:
        return []

    # Get all verb lemmas of the word
    verb_lemmas = [l for s in verb_synsets \
                   for l in s.lemmas if s.name.split('.')[1] == 'v']

    # Get related forms
    derivationally_related_forms = [(l, l.derivationally_related_forms()) \
                                    for l in    verb_lemmas]

    # filter only the nouns
    related_noun_lemmas = [l for drf in derivationally_related_forms \
                           for l in drf[1] if l.synset.name.split('.')[1] == 'n']

    # Extract the words from the lemmas
    words = [l.name for l in related_noun_lemmas]
    len_words = len(words)

    # Build the result in the form of a list containing tuples (word, probability)
    result = [(w, float(words.count(w))/len_words) for w in set(words)]
    result.sort(key=lambda w: -w[1])

    # return all the possibilities sorted by probability
    return result