Marie and Bert


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Marie and Bert is a Knowledge Graph Question Answering (KGQA) system for chemistry implemented on hybrid knowledge graph embeddings. Unlike other existing designs, the system operates on multiple embedding spaces, which use various embedding methods, and queries the embedding spaces in parallel. With the answers returned from multiple embedding spaces, the system leverages a score alignment model to adjust the answer scores and re-rank the answers. Further, the system implements an algorithm to derive implicit multi-hop relations to improve multi-hop QA. The system also implements a BERT-based bi-directional entity-linking model to enhance the robustness and accuracy of the entity-linking module. The system uses a joint numerical embedding model to efficiently handle numerical filtering questions. Further, it is capable of invoking semantic agents to perform dynamic calculations autonomously. Finally, the KGQA system handles numerous chemical reaction mechanisms using semantic parsing supported by a Linked Data Fragment server.

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