jishnujayakumar/MLRC2020-EmbedKGQA
This is the code for the MLRC2020 challenge w.r.t. the ACL 2020 paper Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
This project helps researchers and practitioners in natural language processing (NLP) to improve question-answering systems over knowledge graphs. It takes a knowledge graph and natural language questions as input, and outputs accurate answers to complex, multi-hop questions. This is for AI/ML researchers focused on knowledge graph-based question answering.
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Use this if you are developing or evaluating advanced question-answering models that need to retrieve information across multiple steps within a knowledge graph.
Not ideal if you are looking for a ready-to-use, off-the-shelf question-answering application for end-users, or if your questions do not require complex, multi-hop reasoning over structured data.
Stars
25
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 25, 2021
Commits (30d)
0
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curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/jishnujayakumar/MLRC2020-EmbedKGQA"
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