{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Recognizes and extracts numbers with units (age, currency, dimensions, temperature) from text in multiple languages, resolving them to standardized values.","skillfed_tags":["entity-extraction","multilingual-nlp","unit-parsing"],"use_cases":["Extract currency amounts and units from financial documents or user input for chatbots and virtual assistants","Parse measurement specifications in product descriptions or technical documentation across multiple languages","Normalize age and other personal metrics from user-provided text in healthcare or fitness applications","Identify temperature readings and unit conversions in weather data or IoT sensor logs","Build multilingual NLP pipelines that need to recognize and standardize numeric quantities with units"],"what_it_does":"This package extracts and normalizes numbers paired with units from natural language text. It handles quantities expressed in words by identifying the numeric value and its associated unit, then resolving both to a canonical form. The package is part of Microsoft's Recognizers-Text ecosystem and powers entity recognition in LUIS, Power Virtual Agents, and the Bot Framework.\n\nThe module depends on recognizers-text and recognizers-text-number as its core runtime dependencies, plus regex for pattern matching. It supports full recognition in Chinese, English, French, Spanish, Portuguese, German, Italian, Turkish, Hindi, and Dutch, with partial support for Japanese, Korean, Arabic, and Swedish. The package is distributed as a pure-Python wheel with low installation friction.","worth_installing":"Yes, with conditions. The package is permissively licensed, has low install friction, and addresses a real need for multilingual unit extraction. However, it is in alpha status with no releases since November 2019\u2014verify that the recognition accuracy and language coverage meet your use case before committing to production. The active repository and 1793 stars suggest ongoing community interest, but the stale release cycle warrants caution."},"id":"recognizers-text-number-with-unit","links":{"html":"https://skillfed.io/packages/recognizers-text-number-with-unit","md":"https://skillfed.io/packages/recognizers-text-number-with-unit.md","pypi":"https://pypi.org/project/recognizers-text-number-with-unit/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2019-11-12","license_spdx":null,"license_treatment":"permissive","name":"recognizers-text-number-with-unit","python_support":"unspecified","summary":"recognizers-text-number-with-unit README"},"popularity":{"monthly_downloads":99743,"position":13012,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.2a2"}