--- id: recognizers-text-choice version: "1.0.2a2" license: MIT license_treatment: permissive maintenance: active --- # recognizers-text-choice — recognizers-text-choice README License: permissive · Maintenance: active · Downloads: 98.3K/mo ## What it is and what it does recognizers-text-choice is a Python binding for Microsoft's Recognizers-Text library, specializing in extracting and normalizing structured entities from unstructured text. It focuses on choice/boolean entity recognition as part of the broader Recognizers-Text ecosystem, which powers LUIS, Power Virtual Agents, and Microsoft Bot Framework. The package depends on recognizers-text for core recognition infrastructure, regex for pattern matching, and grapheme for proper handling of complex Unicode characters. The library is designed for natural language processing pipelines where you need to identify and resolve boolean choices or similar categorical entities in multiple languages. It's particularly useful in conversational AI, chatbot development, and text analytics applications where standardized entity extraction across languages is required. The package remains in alpha status, indicating it may still be evolving, though the underlying Recognizers-Text project is mature and widely deployed in Microsoft services. Use it for: - Extract yes/no or true/false answers from user input in chatbots and conversational agents - Normalize boolean choice entities in multilingual text analytics pipelines - Preprocess user responses for LUIS or other language understanding services - Parse choice-based entities in customer support or survey response automation - Build language-agnostic entity extraction for international chatbot applications ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. Recognizes and resolves entities like numbers, units, and date/time expressions in text across multiple languages, including full support for Chinese, English, French, Spanish, Portuguese, German, Italian, Turkish, Hindi, and Dutch. Yes, with conditions. The package has low install friction, permissive licensing, and active maintenance. However, its alpha status and lack of recent releases (latest from November 2019) suggest it may not be actively evolving. Install it if you need multilingual choice entity recognition as part of a Microsoft Recognizers-Text integration; verify that the alpha designation doesn't conflict with your production requirements. ## Install pip install recognizers-text-choice uv add recognizers-text-choice poetry add recognizers-text-choice ## Installing recognizers-text-choice Before you install: Low install friction with a pure-Python wheel. The package is actively maintained with recent commits and has been in active development since its initial release. It depends on recognizers-text, regex, and grapheme—all stable, widely-used libraries. License in practice: MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects. Quickstart: pip install recognizers-text-choice from recognizers_text_choice import recognize_choice result = recognize_choice("yes", "en-us") Verify before relying: - Whether the package is production-ready despite alpha classification (Development Status :: 3 - Alpha) - Specific performance characteristics or accuracy metrics for entity recognition across supported languages - Whether Python 3.6 support (listed in classifiers) is still maintained or if newer versions are required ## Package facts - License: MIT (permissive) - Python support: unspecified - Install friction: low - Maintenance: active - Downloads: 98.3K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags entity recognition multilingual, date time number extraction, nlp entity recognizer, text parsing language understanding, currency unit recognition, named entity extraction, entity-extraction, multilingual-nlp, conversational-ai [View on SkillFed](https://skillfed.io/packages/recognizers-text-choice) · [View on PyPI](https://pypi.org/project/recognizers-text-choice/)