# microsoft/Recognizers-Text

Microsoft.Recognizers.Text provides recognition and resolution of numbers, units, date/time, etc. in multiple languages (ZH, EN, FR, ES, PT, DE, IT, TR, HI, NL. Partial support for JA, KO, AR, SV). Packages available at: https://www.nuget.org/profiles/Recognizers.Text, https://www.npmjs.com/~recognizers.text

Repository: https://github.com/microsoft/Recognizers-Text
Canonical: https://ross.abutalabs.com/products/recognizers-text
Language: C#
License: MIT
License Family: permissive
Topics: nlp, datetime, timex, parser-library, ner, hacktoberfest, date, entity-extraction, number-expression, numbers, numex, parser, time, time-expression, time-expression-recognition, datetime-normalization-and-resolution
Last push: 2026-04-17T06:19:03+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 77, release rhythm 28, longevity 100
- inputs: {"age_days": 3425, "days_push": 138, "days_rel": 566, "gap_med": 37, "n_releases_24m": 4}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1794, forks 434 (observed 2026-08-28T04:05:37.351269+00:00)

## What it is
Microsoft.Recognizers-Text is a multilingual library for recognizing and resolving entities such as numbers, units, and date/time expressions in text. It is available as packages for .NET, JavaScript/TypeScript, Python, and Java, and powers pre-built entities in LUIS, Power Virtual Agents, and the Microsoft Bot Framework.

## Use cases
- extract dates and times from user text in a chatbot
- parse numbers and units from natural language input
- recognize entities in multiple languages like English, Chinese, and Spanish
- normalize datetime expressions to structured values
- add pre-built entity recognition to a LUIS or Bot Framework app
- extract number expressions from free-form text

## When to choose
- you need robust, multilingual extraction of numbers, units, or date/time from text
- you are building a bot or conversational app on Microsoft Bot Framework or LUIS
- you want a deterministic parser rather than an ML model for entity extraction
- you need packages across .NET, JavaScript, Python, or Java

## When to avoid
- you need general-purpose NER for people, organizations, or locations
- you need an ML-based or deep-learning entity extractor
- your target language is only partially supported (e.g., Japanese, Korean, Arabic, Swedish) and support quality matters
- you need a single-language-only lightweight solution

## Facets
- artifact type: library
- maturity: stable
- function: nlp, parser, sdk
- domain: developer-tools, apis
- platform: dotnet, python, jvm, cross-platform
- tags: entity-extraction, named-entity-recognition, datetime-recognition, number-recognition, multilingual, bot-framework, natural-language-processing, nodejs

## Member repositories
- microsoft/Recognizers-Text (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:37.351269+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:22:54.459632+00:00, confidence not recorded.
  - readme: https://github.com/microsoft/Recognizers-Text (fetched 2026-08-28T04:05:37.351269+00:00, sha cdcdbb38d459)
- Data as of 2026-08-30T08:39:29.467469+00:00.