README.md

metadata

title: ChEMU NER Demo
emoji: ⚗️
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.49.1
python_version: '3.12'
app_file: app.py
pinned: false
license: cc-by-nc-3.0
short_description: BioBERT-based NER for chemical patents (ChEMU 2020)

ChEMU NER Demo

Interactive demo for a BioBERT-based named entity recognition model fine-tuned on the ChEMU 2020 Task 1 chemical patent corpus.

The model (mpkato/chemu-biobert-ner) extracts 10 reaction-step entity types from patent text:

• Compounds: STARTING_MATERIAL, REAGENT_CATALYST, REACTION_PRODUCT, SOLVENT, OTHER_COMPOUND
• Conditions: TEMPERATURE, TIME
• Yields: YIELD_PERCENT, YIELD_OTHER
• Labels: EXAMPLE_LABEL

Held-out dev exact-match micro-F1 ≈ 0.95.

Usage

Paste any reaction description into the text box and click Extract entities. Three quick examples are provided at the bottom.

License

Training data (ChEMU 2020) is licensed under CC BY-NC 3.0; this demo and the underlying model are therefore for non-commercial research use only.