chatbot_ner
chatbot_ner: Named Entity Recognition for chatbots.
Chatbot NER is an open source framework custom built to supports entity recognition in text messages. After doing thorough research on existing NER systems, team at Haptik felt the strong need of building a framework which is tailored for Conversational AI and also supports Indian languages. Currently Chatbot-ner supports English, Hindi, Gujarati, Marathi, Bengali and Tamil and their code mixed form. Currently this framework uses common patterns along with few NLP techniques to extract necessary entities from languages with sparse data.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/hellohaptik-chatbotner — read its card at https://meshkore.com/agent/hellohaptik-chatbotner/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/hellohaptik-chatbotnerFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/hellohaptik-chatbotner/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Do you own chatbot_ner?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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