Papers › Complex Temporal Question Answering on Knowledge Graphs

Complex Temporal Question Answering on Knowledge Graphs

18 Sep 2021arXiv:2109.08935archive 2025-07-28

Zhen Jia, Soumajit Pramanik, Rishiraj Saha Roy, Gerhard Weikum

Question answering over knowledge graphs (KG-QA) is a vital topic in IR. Questions with temporal intent are a special class of practical importance, but have not received much attention in research. This work presents EXAQT, the first end-to-end system for answering complex temporal questions that have multiple entities and predicates, and associated temporal conditions. EXAQT answers natural language questions over KGs in two stages, one geared towards high recall, the other towards precision at top ranks. The first step computes question-relevant compact subgraphs within the KG, and judiciously enhances them with pertinent temporal facts, using Group Steiner Trees and fine-tuned BERT models. The second step constructs relational graph convolutional networks (R-GCNs) from the first step's output, and enhances the R-GCNs with time-aware entity embeddings and attention over temporal relations. We evaluate EXAQT on TimeQuestions, a large dataset of 16k temporal questions we compiled from a variety of general purpose KG-QA benchmarks. Results show that EXAQT outperforms three state-of-the-art systems for answering complex questions over KGs, thereby justifying specialized treatment of temporal QA.

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zhenjia2017/exaqt officialmentioned in papermentioned on GitHubpytorch report

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Tasks

16kEntity EmbeddingsKnowledge GraphsQuestion Answering

Datasets

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TimeQuestions

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Question Answering TIQ Exaqt P@1 23.2 #7 of 9 Archive leaderboard report
Question Answering TimeQuestions EXAQT P@1 56.5 #4 of 21 Archive leaderboard report

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Methods

AdamAttentionAttention DropoutBERTDense ConnectionsDropoutLayer NormalizationLinear LayerLinear Warmup With Linear DecayMulti-Head AttentionResidual ConnectionSoftmaxWeight DecayWordPiece

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