English

BERTologyNavigator: Advanced Question Answering with BERT-based Semantics

Computation and Language 2024-01-19 v1 Artificial Intelligence

Abstract

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.

Keywords

Cite

@article{arxiv.2401.09553,
  title  = {BERTologyNavigator: Advanced Question Answering with BERT-based Semantics},
  author = {Shreya Rajpal and Ricardo Usbeck},
  journal= {arXiv preprint arXiv:2401.09553},
  year   = {2024}
}

Comments

Accepted in Scholarly QALD Challenge @ ISWC 2023

R2 v1 2026-06-28T14:19:46.847Z