# facebook/duckling

Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.

Repository: https://github.com/facebook/duckling
Canonical: https://ross.abutalabs.com/products/duckling
Language: Haskell
License: NOASSERTION
License Family: other
Last push: 2026-03-15T21:59:35+00:00

## Health v2 (maintenance only)
Score: 55/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 72, release rhythm 8, longevity 100
- inputs: {"age_days": 3472, "days_push": 171, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4313, forks 740 (observed 2026-08-28T04:08:41.764216+00:00)

## What it is
Duckling is a Haskell library that parses natural language text into structured data, extracting entities like dates, times, amounts of money, numbers, and durations. It ships with an example HTTP server so non-Haskell backends can use it via a simple API.

## Use cases
- parse dates and times from user text like 'tomorrow at eight'
- extract amounts of money and durations from chat messages
- recognize credit card numbers and phone numbers in input strings
- build a chatbot that understands quantities and ordinals
- run an entity-extraction HTTP service for a non-Haskell backend

## When to choose
- you need deterministic, rule-based entity extraction without training data
- you're building a conversational assistant that must understand dates, times, money, and numbers
- you want a self-hosted alternative to wit.ai's built-in entities

## When to avoid
- you need general-purpose NLP like sentiment analysis or named-entity recognition of people and places
- your stack can't run Haskell or host a separate parsing service
- you need ML-based extraction that adapts to novel phrasings

## Facets
- artifact type: library
- maturity: active
- function: nlp, parser, http-server
- domain: developer-tools
- platform: windows
- tags: entity-extraction, haskell, text-parsing, date-parsing, wit-ai, natural-language-processing, linux, macos

## Member repositories
- facebook/duckling (main) score 55

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:41.764216+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 2026-08-29T18:21:47.049655+00:00, confidence not recorded.
  - readme: https://github.com/facebook/duckling (fetched 2026-08-28T04:08:41.764216+00:00, sha fd9b747465d9)
- Data as of 2026-08-30T08:39:29.467469+00:00.