{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Recognizes and resolves date and time entities from text in multiple languages, extracting temporal expressions and normalizing them to structured date/time values.","skillfed_tags":["nlp-entity-extraction","multilingual","date-time-parsing"],"use_cases":["Extract temporal references from user input in chatbots or virtual assistants to schedule tasks or set reminders.","Parse date/time mentions in customer support tickets or logs to identify when issues occurred.","Normalize temporal expressions in multilingual documents for downstream analysis or database storage.","Build NLP preprocessing pipelines that need to identify and resolve date/time entities before further processing.","Augment text analytics workflows to tag and extract temporal context from unstructured text."],"what_it_does":"recognizers-text-date-time is a specialized component of Microsoft's Recognizers-Text suite that extracts and normalizes date and time expressions from natural language text. It handles temporal phrases like \"tomorrow\", \"next Friday\", \"3 PM\", and \"in two weeks\", converting them into structured date/time values. The package supports multiple languages including English, Chinese, French, Spanish, Portuguese, German, Italian, Turkish, Hindi, and Dutch, with partial support for Japanese, Korean, Arabic, and Swedish.\n\nThe package is designed as a building block for NLP pipelines, chatbots, and language understanding systems. It depends on recognizers-text as its foundation, along with regex and datedelta for pattern matching and date arithmetic. As an alpha-stage library that has not released since 2019, it represents a snapshot of the recognizer suite's date-time capabilities; the upstream repository remains maintained, but this PyPI package itself is not actively versioned.","worth_installing":"Yes, with conditions. The package is stable and permissively licensed, with low install friction and no known vulnerabilities. However, it is in alpha status and has not been released since 2019, which may indicate incomplete language support or unresolved issues. Install if you need multilingual date/time entity extraction in a non-critical context or as part of a larger Recognizers-Text integration; avoid if you require active maintenance or guaranteed stability for production systems."},"id":"recognizers-text-date-time","links":{"html":"https://skillfed.io/packages/recognizers-text-date-time","md":"https://skillfed.io/packages/recognizers-text-date-time.md","pypi":"https://pypi.org/project/recognizers-text-date-time/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2019-11-12","license_spdx":null,"license_treatment":"permissive","name":"recognizers-text-date-time","python_support":"unspecified","summary":"recognizers-text-date-time README"},"popularity":{"monthly_downloads":99211,"position":13035,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.2a2"}