BERTologyNavigator: Advanced Question Answering with BERT-based Semantics
CoRR(2024)
摘要
The development and integration of knowledge graphs and language models has
significance in artificial intelligence and natural language processing. In
this study, we introduce the BERTologyNavigator – a two-phased system that
combines relation extraction techniques and BERT embeddings to navigate the
relationships within the DBLP Knowledge Graph (KG). Our approach focuses on
extracting one-hop relations and labelled candidate pairs in the first phases.
This is followed by employing BERT's CLS embeddings and additional heuristics
for relation selection in the second phase. Our system reaches an F1 score of
0.2175 on the DBLP QuAD Final test dataset for Scholarly QALD and 0.98 F1 score
on the subset of the DBLP QuAD test dataset during the QA phase.
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