搜集、整理、发布 中文 自然语言处理 语料/数据集，与 有志之士 共同 促进 中文 自然语言处理 的 发展。
Les fonctionnalités principales de sophonplus/chinesenlpcorpus sont : Natural Language Processing, Sentiment Analysis, Text Classification, Corpus and Datasets, Natural Language Corpora.
Les alternatives open-source à sophonplus/chinesenlpcorpus incluent : wainshine/chinese-names-corpus — This project is a curated collection of Chinese names, surnames, and kinship terms designed for linguistic analysis… zhangyics/chinese-abbreviation-dataset — This is a corpus of Chinese abbreviation, including negative full forms. embedding/chinese-word-vectors — This project is a collection of pre-trained dense and sparse word vectors trained on diverse Chinese corpora. It… thunlp/openclap — Open Chinese Language Pre-trained Model Zoo. ymcui/chinese-bert-wwm — Chinese-BERT-wwm is a pre-trained transformer model and encoder designed for Chinese natural language processing. It… wooorm/franc — Franc is a natural language detection library and command line identifier used to determine the written language of a…
This project is a curated collection of Chinese names, surnames, and kinship terms designed for linguistic analysis and natural language processing. It functions as a multilingual name dataset and a training resource for named entity recognition, providing a unified repository of names across Chinese, Japanese, and English languages. The project includes a synthetic name generator that creates realistic person names by applying analyzed naming patterns and demographic data. It also provides a cleaned Chinese idiom lexicon gathered and deduplicated from multiple sources. The available data su
This project is a collection of pre-trained dense and sparse word vectors trained on diverse Chinese corpora. It serves as a library of linguistic representations and an NLP vector dataset designed to improve the accuracy of semantic and morphological analysis in text models. The collection provides corpus-specific representations and utilizes n-gram co-occurrence modeling to capture diverse linguistic patterns. It includes a hybrid of dense-sparse vectors to balance computational efficiency and semantic precision. The project covers semantic vector search and the development of Chinese natu
Chinese-BERT-wwm is a pre-trained transformer model and encoder designed for Chinese natural language processing. It converts Chinese text into dense vector representations to be used across various natural language processing applications. The model utilizes a whole word masking strategy during pre-training, masking entire words rather than individual characters. This approach is designed to improve the capture of semantic meaning and language structure within Chinese datasets. The project covers a range of downstream tasks including text classification, sequence labeling, and reading compr
