# BERTologyNavigator: Advanced Question Answering with BERT-based Semantics

Source: [BERTologyNavigator: Advanced Question Answering with BERT-based Semantics](<https://www.sota2.com/research/paper/68fa71e11e209131cea5389f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:29:09.138Z

Authors: Shreya Rajpal, Ricardo Usbeck (1) \_\_INSTITUTION\_2\_\_ Universit\\"at Hamburg, Hamburg, Germany, (2) Vellore Institute of Technology, Vellore, Tamil Nadu, India)

Published: 2024-01-17T19:11:30.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2401.09553>)

[PDF](<https://arxiv.org/pdf/2401.09553.pdf>)