In this work, we present VNLP: the first dedicated, complete, open-source,
well-documented, lightweight, production-ready, state-of-the-art Natural
Language Processing (NLP) package for the Turkish language. It contains a wide
variety of tools, ranging from the simplest tasks, such as sentence splitting
and text normalization, to the more advanced ones, such as text and token
classification models. Its token classification models are based on "Context
Model", a novel architecture that is both an encoder and an auto-regressive
model. NLP tasks solved by VNLP models include but are not limited to Sentiment
Analysis, Named Entity Recognition, Morphological Analysis \& Disambiguation
and Part-of-Speech Tagging. Moreover, it comes with pre-trained word embeddings
and corresponding SentencePiece Unigram tokenizers. VNLP has an open-source
GitHub repository, ReadtheDocs documentation, PyPi package for convenient
installation, Python and command-line API and a demo page to test all the
functionality. Consequently, our main contribution is a complete, compact,
easy-to-install and easy-to-use NLP package for Turkish.

这篇论文介绍了 VNLP：第一个专门为土耳其语设计的完整、开源、文档齐全、轻量级、成熟的自然语言处理（NLP）工具包。该工具包包含了各种各样的工具，从最简单的任务如句子分割和文本规范化，到更高级的任务如文本和标记分类模型。VNLP 的标记分类模型基于一种称为 “Context Model” 的新型架构，既是编码器又是自回归模型。VNLP 解决的 NLP 任务包括但不限于情感分析、命名实体识别、形态分析和消歧和词性标注。此外，它还提供了预训练的词嵌入和相应的 SentencePiece Unigram 标记器。VNLP 具有开源的 GitHub 仓库、ReadtheDocs 文档、PyPi 包便于安装、Python 和命令行 API 以及一个演示页面来测试所有功能。因此，我们的主要贡献是一个完整、紧凑、易于安装和使用的土耳其语 NLP 工具包。