# Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs

Source: [Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs](<https://www.sota2.com/research/paper/68fa6f461e209131cea44aea>)

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

Data updated: 2025-12-22T09:34:20.765Z

Authors: Wentao Ding, Hao Chen, Huayu Li, Yuzhong Qu

Published: 2022-10-10T08:40:28.000Z

## Abstract

Answering factual questions with temporal intent over knowledge graphs (temporal KGQA) attracts rising attention in recent years. In the generation of temporal queries, existing KGQA methods ignore the fact that some intrinsic connections between events can make them temporally related, which may limit their capability. We systematically analyze the possible interpretation of temporal constraints and conclude the interpretation structures as the Semantic Framework of Temporal Constraints, SF-TCons. Based on the semantic framework, we propose a temporal question answering method, SF-TQA, which generates query graphs by exploring the relevant facts of mentioned entities, where the exploring process is restricted by SF-TCons. Our evaluations show that SF-TQA significantly outperforms existing methods on two benchmarks over different knowledge graphs.

## 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/2210.04490>)

[PDF](<https://arxiv.org/pdf/2210.04490.pdf>)