# Kyubyong/nlp_tasks

Natural Language Processing Tasks and References

Repository: https://github.com/Kyubyong/nlp_tasks
Canonical: https://ross.abutalabs.com/products/nlp_tasks
License: Apache-2.0
License Family: permissive
Topics: language, natural-language-processing, nlp
Last push: 2018-09-20T03:10:58+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3253, "days_push": 2904, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3009, forks 537 (observed 2026-08-28T04:07:37.764271+00:00)

## What it is
A curated map of natural language processing tasks with selected references, including papers, projects, datasets, and challenges. It serves as a starting point for exploring the breadth of the NLP field, biased toward recent deep learning work.

## Use cases
- find papers on a specific NLP task
- get an overview of the NLP field at a glance
- find datasets for speech recognition research
- discover open-source NLP projects to study
- find challenges and benchmarks for text summarization
- start learning about coreference resolution

## When to choose
- you want a broad survey of NLP tasks with curated references
- you need a starting point of papers and datasets for a new NLP topic
- you prefer human-curated lists over search engines

## When to avoid
- you need up-to-date references on modern LLM-era NLP
- you need runnable code or a library rather than a reference list
- you need exhaustive coverage of every NLP subfield

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: nlp, documentation
- domain: machine-learning, tutorials
- platform: cross-platform
- tags: awesome-list, reference-collection, curated-list, deep-learning-papers, datasets, natural-language-processing

## Member repositories
- Kyubyong/nlp_tasks (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:37.764271+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 2026-08-29T18:47:02.824002+00:00, confidence not recorded.
  - readme: https://github.com/Kyubyong/nlp_tasks (fetched 2026-08-28T04:07:37.764271+00:00, sha 07634b90ff93)
- Data as of 2026-08-30T08:39:29.467469+00:00.