{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/question-answering-over-temporal-knowledge","title":"Question Answering Over Temporal Knowledge Graphs","arxiv_id":"2106.01515","date":"2021-06-03","proceeding":"ACL 2021 5","authors":["Apoorv Saxena","Soumen Chakrabarti","Partha Talukdar"],"abstract":"Temporal Knowledge Graphs (Temporal KGs) extend regular Knowledge Graphs by providing temporal scopes (start and end times) on each edge in the KG. While Question Answering over KG (KGQA) has received some attention from the research community, QA over Temporal KGs (Temporal KGQA) is a relatively unexplored area. Lack of broad coverage datasets has been another factor limiting progress in this area. We address this challenge by presenting CRONQUESTIONS, the largest known Temporal KGQA dataset, clearly stratified into buckets of structural complexity. CRONQUESTIONS expands the only known previous dataset by a factor of 340x. We find that various state-of-the-art KGQA methods fall far short of the desired performance on this new dataset. In response, we also propose CRONKGQA, a transformer-based solution that exploits recent advances in Temporal KG embeddings, and achieves performance superior to all baselines, with an increase of 120% in accuracy over the next best performing method. Through extensive experiments, we give detailed insights into the workings of CRONKGQA, as well as situations where significant further improvements appear possible. In addition to the dataset, we have released our code as well.","url_abs":"https://arxiv.org/abs/2106.01515v1","url_pdf":"https://arxiv.org/pdf/2106.01515v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"question-answering-over-temporal-knowledge","repo_url":"https://github.com/apoorvumang/CronKGQA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"question-answering-over-temporal-knowledge","repo_url":"https://github.com/cmavro/tempoqr","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"knowledge-graphs","task_name":"Knowledge Graphs"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[{"slug":"cronquestions","name":"CronQuestions","full_name":""}],"methods_introduced":[],"results":[{"leaderboard":"/sota/question-answering-on-complex-cronquestions","task":"Question Answering","dataset":"Complex-CronQuestions","model":"CronKGQA","rank_in_archive_order":4,"of":4,"metrics":{"Hits@1":"26.6"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-cronquestions","task":"Question Answering","dataset":"CronQuestions","model":"CronKGQA","rank_in_archive_order":18,"of":29,"metrics":{"Hits@1":"64.7"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-multitq","task":"Question Answering","dataset":"MultiTQ","model":"CronKGQA","rank_in_archive_order":5,"of":11,"metrics":{"Hits@1":"27.9","Hits@10":"63.5"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-tiq","task":"Question Answering","dataset":"TIQ","model":"CronKGQA","rank_in_archive_order":9,"of":9,"metrics":{"P@1":"0.6"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-timequestions","task":"Question Answering","dataset":"TimeQuestions","model":"CRONKGQA","rank_in_archive_order":16,"of":21,"metrics":{"P@1":"39.5"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2106.01515","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.01515"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/apoorvumang/CronKGQA","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/cmavro/tempoqr","reach":{"status":"ok"}}],"summary":{"unverified":2},"by_repo_kind":{"official":{"samples":1,"ran":0,"repositories":1},"listed":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"ce43fb1f5889dbdb","entry":"QA_TempoQR","repo":"cmavro/tempoqr","repo_kind":"listed","path":"qa_tempoqr.py","file_url":"https://github.com/cmavro/tempoqr/blob/HEAD/qa_tempoqr.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"ce43fb1f5889dbdb"}},{"code_sha256_prefix":"1537434fd7d7cf86","entry":"QA_model_EmbedKGQA","repo":"apoorvumang/CronKGQA","repo_kind":"official","path":"qa_models.py","file_url":"https://github.com/apoorvumang/CronKGQA/blob/HEAD/qa_models.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1537434fd7d7cf86"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}