Papers › TempoQR: Temporal Question Reasoning over Knowledge Graphs
TempoQR: Temporal Question Reasoning over Knowledge Graphs
Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Soji Adeshina, Phillip R. Howard, Tetiana Grinberg, Nagib Hakim, George Karypis
Knowledge Graph Question Answering (KGQA) involves retrieving facts from a Knowledge Graph (KG) using natural language queries. A KG is a curated set of facts consisting of entities linked by relations. Certain facts include also temporal information forming a Temporal KG (TKG). Although many natural questions involve explicit or implicit time constraints, question answering (QA) over TKGs has been a relatively unexplored area. Existing solutions are mainly designed for simple temporal questions that can be answered directly by a single TKG fact. This paper puts forth a comprehensive embedding-based framework for answering complex questions over TKGs. Our method termed temporal question reasoning (TempoQR) exploits TKG embeddings to ground the question to the specific entities and time scope it refers to. It does so by augmenting the question embeddings with context, entity and time-aware information by employing three specialized modules. The first computes a textual representation of a given question, the second combines it with the entity embeddings for entities involved in the question, and the third generates question-specific time embeddings. Finally, a transformer-based encoder learns to fuse the generated temporal information with the question representation, which is used for answer predictions. Extensive experiments show that TempoQR improves accuracy by 25--45 percentage points on complex temporal questions over state-of-the-art approaches and it generalizes better to unseen question types.
In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Question Answering | Complex-CronQuestions | TempoQR | Hits@1 | 79.2 | #2 of 4 | Archive leaderboard | report |
| Question Answering | Complex-CronQuestions | EntityQR | Hits@1 | 42.5 | #3 of 4 | Archive leaderboard | report |
| Question Answering | CronQuestions | TempoQR-Hard | Hits@1 | 91.8 | #9 of 29 | Archive leaderboard | report |
| Question Answering | CronQuestions | TempoQR-Soft | Hits@1 | 79.9 | #14 of 29 | Archive leaderboard | report |
| Question Answering | CronQuestions | EntityQR | Hits@1 | 74.5 | #17 of 29 | Archive leaderboard | report |
| Question Answering | CronQuestions | BERT | Hits@1 | 24.3 | #24 of 29 | Archive leaderboard | report |
| Question Answering | TIQ | TempoQR | P@1 | 1.1 | #8 of 9 | Archive leaderboard | report |
| Question Answering | TimeQuestions | TempoQR | P@1 | 43.8 | #12 of 21 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections