pythainlp.benchmarks

Introduction

The pythainlp.benchmarks module is a collection of utility functions designed for benchmarking tasks related to Thai Natural Language Processing (NLP). Currently, the module includes tools for word tokenization benchmarking. Please note that additional benchmarking tasks will be incorporated in the future.

Tokenization

Word tokenization is a fundamental task in NLP, and it plays a crucial role in various applications, such as text analysis and language processing. The pythainlp.benchmarks module offers a set of functions to assist in the benchmarking and evaluation of word tokenization methods.

Quality Evaluation

The quality of word tokenization can significantly impact the accuracy of downstream NLP tasks. To assess the quality of word tokenization, the module provides a qualitative evaluation using various metrics and techniques.

../_images/evaluation.png — Qualitative evaluation of word tokenization.

Functions

Usage

To make use of these benchmarking functions, you can follow the provided examples and guidelines in the official PyThaiNLP documentation. These tools are invaluable for researchers, developers, and anyone interested in improving and evaluating Thai word tokenization methods.