Rule-based named-entity recognition for English text, from patterns and word lists rather than a trained model: persons, organisations, places, dates, money, percentages, emails, URLs and products, with character offsets. Best on clean, well-capitalised text; it misses names off its lists. POST /v1/ner with {text}. Pay per request in USDC; no account, no API key.
| Network | Scheme | Amount | Pay To |
|---|---|---|---|
| Base | exact | $0.005000 USDC | 0xF732...B829 |