reckoner', 'figurer', 'estimator', 'computer'] 反义词处理 也可以用同样的方法得到反义词： 1from nltk.corpus import wordnet 2antonyms...= [] 3for syn in wordnet.synsets("small"): 4 for l in syn.lemmas(): 5 if l.antonyms(): 6...antonyms.append(l.antonyms()[0].name()) 7print(antonyms) 输出: 1['large', 'big', 'big'] 词干提取 语言形态学和信息检索里
reckoner', 'figurer', 'estimator', 'computer'] 反义词处理 也可以用同样的方法得到反义词： from nltk.corpus import wordnet antonyms...= [] for syn in wordnet.synsets("small"): for l in syn.lemmas(): if l.antonyms(): antonyms.append...(l.antonyms()[0].name()) print(antonyms) 输出: ['large', 'big', 'big'] 词干提取 语言形态学和信息检索里，词干提取是去除词缀得到词根的过程
from nltk.corpus import wordnet antonyms = [] for syn in wordnet.synsets("small"): for l in syn.lemmas...(): if l.antonyms(): antonyms.append(l.antonyms()[0].name()) print(antonyms) 输出是： [‘large’
verbal reasoning questions, which are based around analogies, classifications, as well as synonyms and antonyms...And questions looking for synonyms and antonyms are like these: Which word is closest to IRRATIONAL?
reckoner', 'figurer', 'estimator', 'computer'] 反义词处理 也可以用同样的方法得到反义词： from nltk.corpus import wordnet antonyms...= [] for syn in wordnet.synsets("small"): for l in syn.lemmas(): if l.antonyms():...antonyms.append(l.antonyms()[0].name()) print(antonyms) 输出: ['large', 'big', 'big'] 词干提取 语言形态学和信息检索里，
from nltk.corpus import wordnet antonyms = [] for syn in wordnet.synsets("small"): for l in syn.lemmas...(): if l.antonyms(): antonyms.append(l.antonyms()[0].name()) print(antonyms) 输出是：
TextBlob 获取反义词列表 from textblob import TextBlob from textblob import Word text_word = Word('safe') antonyms...= set() for synset in text_word.synsets: for lemma in synset.lemmas(): if lemma.antonyms...(): antonyms.add(lemma.antonyms()[0].name()) print(antonyms) Output: {'dangerous
KDD, 2004.该方法步骤如下： Create positive (“good”) and negative seed-words (“terrible”) Find Synonyms and Antonyms...Positive Set: Add synonyms of positive words (“well”) and antonyms of negative words Negative Set:...Add synonyms of negative words (“awful”) and antonyms of positive words (”evil”) Repeat, following...Using “and” and “but” Using words that occur nearby in the same document Using WordNet synonyms and antonyms
Proceedings of KDD, 2004 步骤: 有一小部分 positive/negative seed-words 从 WordNet 中找到 seed-words 的同义词(synonyms)和反义词(antonyms...“and” and “but” • Using words that occur nearby in the same document • Using WordNet synonyms and antonyms
"displayText": "Loans" }], "seeAlso" : [], "synonyms" : [], "antonyms
这些词形是同义词，然后你可以使用.antonyms找到词形的反义词。...因此，我们可以填充一些列表，如： synonyms = [] antonyms = [] for syn in wordnet.synsets("good"): for l in syn.lemmas...(): synonyms.append(l.name()) if l.antonyms(): antonyms.append(l.antonyms...()[0].name()) print(set(synonyms)) print(set(antonyms)) ''' {'beneficial', 'just', 'upright', 'thoroughly
classification ---小窗口上下文文本分类器 问题: in general，很少对单个单词进行分类 ambiguity arise in context，一词多义的问题 example1：auto-antonyms
使用这种方法后，作者在 SimVerb-3500 中的九个类别的同义词（SYNONYMS, ANTONYMS, HYPER/HYPONYMS, COHYPONYM，NONE ）进行了对比，对比结果如表
langchain.prompts.example_selector import LengthBasedExampleSelector # These are a lot of examples of a pretend task of creating antonyms
顺便说一句，在版本12.0中，我们添加了各种小的“自然语言便利功能”，如Synonyms 和 Antonyms： ? 计算化学 12.0版在计算化学方面带来了“惊喜”。
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