Feb. 20, 2024, 5:51 a.m. | Xinbang Dai, Huiying Li, Guilin Qi

cs.CL updates on arXiv.org arxiv.org

arXiv:2402.11542v1 Announce Type: new
Abstract: Spatio-temporal knowledge graphs (STKGs) extend the concept of knowledge graphs (KGs) by incorporating time and location information. While the research community's focus on Knowledge Graph Question Answering (KGQA), the field of answering questions incorporating both spatio-temporal information based on STKGs remains largely unexplored. Furthermore, a lack of comprehensive datasets also has hindered progress in this area. To address this issue, we present STQAD, a dataset comprising 10,000 natural language questions for spatio-temporal knowledge graph question …

abstract arxiv community concept cs.ai cs.cl datasets focus graph graphs information knowledge knowledge graph knowledge graphs location question question answering questions research research community temporal type

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Global Data Architect, AVP - State Street Global Advisors

@ State Street | Boston, Massachusetts

Data Engineer

@ NTT DATA | Pune, MH, IN