Stanford Word Segmenter
The Stanford Word Segmenter effectively tokenizes Arabic and Chinese text, facilitating essential pre-processing for various NLP tasks. It adeptly handles Arabic's root-and-template structure, separating clitics to enhance syntactic analysis. For Chinese, it employs established segmentation standards, ensuring accurate word splitting. Java-based, it supports extensible features and dual licensing options.
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Top Stanford Word Segmenter Features
- Supports Arabic and Chinese
- Clitic segmentation for Arabic
- Two segmentation standards for Chinese
- K-best segmentations output
- Java API included
- Command-line invocation components
- Open source under GPL
- Lexicon feature integration
- Penn Arabic Treebank standard
- Chinese Penn Treebank standard
- Peking University standard
- External lexicon features
- Memory optimization options
- Support for longer documents
- Comprehensive documentation available
- Community support via mailing lists
- Commercial licensing available
- Frequent updates and maintenance.
