Code for ACL 2019 Paper: "COMET: Commonsense Transformers for Automatic Knowledge Graph Construction" https://arxiv.org/abs/1906.05317

Knowledge-Infused Topic Model (KITM) for empathetic dialogue generation, integrating topic modeling with commonsense reasoning from COMET. Official implementation of our APSIPA ASC 2025 paper.

COMET-ATOMIC ja's translate demonstration in English and Chinese, A commonsense knowledge graph on events translate from Waseda University.

Paper reproduction : COMET: Commonsense Transformers for Automatic Knowledge Graph Construction,

This repository contains our path generation framework Co-NNECT, in which we combine two models for establishing knowledge relations and paths between concepts from sentences, as a form of explicitation of implicit knowledge: COREC-LM (COmmonsense knowledge RElation Classification using Language Models), a relation classification system that we developed for classifying commonsense knowledge relations; and COMET, a target prediction system developed by Bosselut et al., 2019.

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data sampling and user interaction for COMET from https://github.com/atcbosselut/comet-commonsense

This project focuses on leveraging COMET-ATOMIC-2020, a commonsense knowledge base, to create schemas for tracking and updating the state of a story as it progresses. A schema is a structured representation used to hold facts and track changes over time, enabling AI systems to perform commonsense reasoning.