{"url":"/dataset/timequestions","name":"TimeQuestions","full_name":null,"description_markdown":"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. We present EXAQT, the first end-to-end system for answering complex temporal questions that have multiple entities and predicates, and associated temporal conditions.","description_withheld":null,"homepage":"https://exaqt.mpi-inf.mpg.de/","introduced_date":"2021-09-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/complex-temporal-question-answering-on","title":"Complex Temporal Question Answering on Knowledge Graphs","first_author":"Zhen Jia","url":null},"license":null,"modalities":[],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"}],"languages":[],"variants":["TimeQuestions"],"data_loaders":[],"num_papers_in_archive":23,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/question-answering-on-timequestions","task":"Question Answering","dataset_variant":"TimeQuestions","rows":21,"metrics":["P@1"],"first_row_in_archive_order":{"model":"TimeR4","paper":null,"metrics":{"P@1":"78.1"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/rag-based-question-answering-over","title":"RAG-based Question Answering over Heterogeneous Data and Text","date":"2024-12-10","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/faithful-temporal-question-answering-over","title":"Faithful Temporal Question Answering over Heterogeneous Sources","date":"2024-02-23","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/openai-s-gpt4-as-coding-assistant","title":"OpenAi's GPT4 as coding assistant","date":"2023-09-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/explainable-conversational-question-answering","title":"Explainable Conversational Question Answering over Heterogeneous Sources via Iterative Graph Neural Networks","date":"2023-05-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/llama-open-and-efficient-foundation-language-1","title":"LLaMA: Open and Efficient Foundation Language Models","date":"2023-02-27","rows_on_this_dataset":1,"code_links":57,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":58,"samples_ran":26,"samples_unverified":32,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/time-aware-multiway-adaptive-fusion-network","title":"Time-aware Multiway Adaptive Fusion Network for Temporal Knowledge Graph Question Answering","date":"2023-02-24","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/graphnet-graph-neural-networks-for-neutrino","title":"GraphNeT: Graph neural networks for neutrino telescope event reconstruction","date":"2022-10-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":0,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/twirgcn-temporally-weighted-graph-convolution","title":"TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs","date":"2022-10-12","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/semantic-framework-based-query-generation-for","title":"Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs","date":"2022-10-10","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/conversational-question-answering-on","title":"Conversational Question Answering on Heterogeneous Sources","date":"2022-04-25","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/training-language-models-to-follow","title":"Training language models to follow instructions with human feedback","date":"2022-03-04","rows_on_this_dataset":1,"code_links":11,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":0,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/tempoqr-temporal-question-reasoning-over","title":"TempoQR: Temporal Question Reasoning over Knowledge Graphs","date":"2021-12-10","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/complex-temporal-question-answering-on","title":"Complex Temporal Question Answering on Knowledge Graphs","date":"2021-09-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/uniqorn-unified-question-answering-over-rdf","title":"UNIQORN: Unified Question Answering over RDF Knowledge Graphs and Natural Language Text","date":"2021-08-19","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/question-answering-over-temporal-knowledge","title":"Question Answering Over Temporal Knowledge Graphs","date":"2021-06-03","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/pullnet-open-domain-question-answering-with","title":"PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text","date":"2019-04-21","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":68,"samples_ran":26,"samples_unverified":42,"pointer_only_for_licence":5,"papers_with_no_sample_that_ran":3,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}