duterscmy/ccks2019-ckbqa-4th-codes
A knowledge-base question answering system for Chinese built with BERT, TensorFlow, and Neo4j graph database.
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This repository contains code for a Chinese open-domain knowledge base question answering system that placed fourth in the CCKS2019 CKBQA competition. The solution references the second-place approach from CCKS2018 COQA and extends it with BERT-based sequence labeling for named entity recognition, semantic matching models, and entity linking over the PKUBASE knowledge graph. Users need to set up a Neo4j graph database locally to run entity extraction and complex question answering pipelines including bridging steps.
Frequently asked
- What is duterscmy/ccks2019-ckbqa-4th-codes?
- A knowledge-base question answering system for Chinese built with BERT, TensorFlow, and Neo4j graph database.
- Is ccks2019-ckbqa-4th-codes open source?
- Yes — duterscmy/ccks2019-ckbqa-4th-codes is an open-source project tracked on heatdrop.
- What language is ccks2019-ckbqa-4th-codes written in?
- duterscmy/ccks2019-ckbqa-4th-codes is primarily written in Python.
- How popular is ccks2019-ckbqa-4th-codes?
- duterscmy/ccks2019-ckbqa-4th-codes has 476 stars on GitHub.
- Where can I find ccks2019-ckbqa-4th-codes?
- duterscmy/ccks2019-ckbqa-4th-codes is on GitHub at https://github.com/duterscmy/ccks2019-ckbqa-4th-codes.