https://github.com/samueldobbie/markup
A web-based document annotation tool, powered by GPT-4 :rocket:
https://github.com/samueldobbie/markup
active-learning annotation-tool data-labeling data-science gpt-4 machine-learning named-entity-recognition natural-language-processing ner nlp sequence-to-sequence text-annotation text-annotation-tool
Last synced: about 2 months ago
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A web-based document annotation tool, powered by GPT-4 :rocket:
- Host: GitHub
- URL: https://github.com/samueldobbie/markup
- Owner: samueldobbie
- License: mit
- Created: 2019-02-21T18:39:57.000Z (about 6 years ago)
- Default Branch: main
- Last Pushed: 2024-01-10T08:22:08.000Z (over 1 year ago)
- Last Synced: 2024-10-28T04:24:08.180Z (6 months ago)
- Topics: active-learning, annotation-tool, data-labeling, data-science, gpt-4, machine-learning, named-entity-recognition, natural-language-processing, ner, nlp, sequence-to-sequence, text-annotation, text-annotation-tool
- Language: TypeScript
- Homepage: https://getmarkup.com
- Size: 79.7 MB
- Stars: 246
- Watchers: 12
- Forks: 32
- Open Issues: 13
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- StarryDivineSky - samueldobbie/markup - 3 提供支持 (A01_文本生成_文本对话 / 其他_文本生成_文本对话)
README
# Markup Annotation Tool for ML and NLP
Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate to predict and suggest complex annotations, and also provides integrated access to common and custom ontologies for concept mapping.
# Key Features
- **Predictive annotation** - Markup's machine learning-powered predictive annotation feature suggests complex annotations as you work, making the process of annotating documents more efficient and saving you valuable time.
- **Integrated ontology access** Markup provides integrated access to a wide range of common ontologies (e.g. UMLS, SNOMED-CT, ICD-10), as well as the ability to upload custom ontologies, for concept mapping.
- **Predictive ontology mapping** - Markup's predictive ontology mapping feature uses machine learning to suggest appropriate mappings to standard and custom terminologies based on the text you're annotating.
- **User-friendly interface** - Whether you're a technical expert or a beginner, Markup's user-friendly interface makes it easy for anyone to start annotating documents with minimal setup.
# Installation
To install and run Markup locally:
1. Clone the repository and install dependencies, `git clone https://github.com/samueldobbie/markup && cd markup && yarn install`
1. Install the [Supabase CLI](https://supabase.com/docs/guides/cli)
1. Start Supabase, `supabase start`. This will generate and output an API URL and anon key. Add both to the `.env.local` file
1. Add an [OpenAI API key](https://platform.openai.com/account/api-keys) to the `.env.local` file (Optional)
1. Run the development server, `yarn start`
1. Open Markup in your web browser, `http://localhost:3000`
# Usage
To get started with Markup, read the [quick start guide](https://getmarkup.com/docs).
# Contributions
Contributions to Markup are appreciated. If you'd like to contribute, please follow these guidelines:
1. Fork the repository
1. Create a new branch for your feature
1. Make your changes
1. Submit a pull request for review
# Support
If you have any questions or need assistance with Markup, you can contact me at [[email protected]](mailto:[email protected]).