Benchmarking Geospatial Question Answering Engines Using the Dataset GEOQUESTIONS1089

被引：6

作者：

Kefalidis, Sergios-Anestis ^{[1
]}

Punjani, Dharmen ^{[2
]}

Tsalapati, Eleni ^{[1
]}

Plas, Konstantinos ^{[1
]}

Pollali, Mariangela ^{[1
]}

Mitsios, Michail ^{[1
]}

Tsokanaridou, Myrto ^{[1
]}

Koubarakis, Manolis ^{[1
]}

Maret, Pierre ^{[2
]}

机构：

[1] Natl & Kapodistrian Univ Athens, Dept Informat & Telecommun, Athens, Greece

[2] Univ St Monnet, St Etienne, France

来源：

SEMANTIC WEB, ISWC 2023, PT II | 2023年 / 14266卷

基金：

欧盟地平线“2020”;

关键词：

D O I：

10.1007/978-3-031-47243-5_15

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present the dataset GeoQuestions1089 for benchmarking geospatial question answering engines. GeoQuestions1089 is the largest such dataset available presently and it contains 1089 questions, their corresponding GeoSPARQL or SPARQL queries and their answers over the geospatial knowledge graph YAGO2geo. We use GeoQuestions1089 to evaluate the effectiveness and efficiency of geospatial question answering engines GeoQA2 (an extension of GeoQA developed by our group) and the system of Hamzei et al. (2021).

引用

页码：266 / 284

页数：19

共 9 条

[1] CoQUAD: a COVID-19 question answering dataset system, facilitating research, benchmarking, and practice
Shaina Raza
Brian Schwartz
Laura C. Rosella
BMC Bioinformatics, 23
[2] CoQUAD: a COVID-19 question answering dataset system, facilitating research, benchmarking, and practice
Raza, Shaina
Schwartz, Brian
Rosella, Laura C.
BMC BIOINFORMATICS, 2022, 23 (01)
[3] A Serbian Question Answering Dataset Created by Using the Web Scraping Technique
Cenic, Aleksandar B.
Stojkovic, Suzana
2023 58TH INTERNATIONAL SCIENTIFIC CONFERENCE ON INFORMATION, COMMUNICATION AND ENERGY SYSTEMS AND TECHNOLOGIES, ICEST, 2023, : 147 - 150
[4] Fine-Tuning BERT for Question and Answering Using PubMed Abstract Dataset
Cheon, Saeyeon
Ahn, Insung
PROCEEDINGS OF 2022 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2022, : 681 - 684
[5] TKGQA Dataset: Using Question Answering to Guide and Validate the Evolution of Temporal Knowledge Graph
Ong, Ryan
Sun, Jiahao
Serban, Ovidiu
Guo, Yi-Ke
DATA, 2023, 8 (03)
[6] AraT5GQA: Arabic Question Answering model using automatic generated dataset
Nakhleh, Saja
Mustafa, Ahmad M.
Najadat, Hassan
2024 15TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION SYSTEMS, ICICS 2024, 2024,
[7] Semi-automated Construction of Complex Knowledge Base Question Answering Dataset Using Large Language Model
Hoang, Lily
Liausvia, Fiona
Liu, Yan
Thanh-Son Nguyen
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES: RESEARCH TRACK, PT V, ECML PKDD 2024, 2024, 14945 : 230 - 248
[8] Natural Language Processing of South African Online Question-Answering Health Forum HIV and AIDS Dataset Using Topic Modeling
Stone, Kyle
Ojo, Sunday
Tu, Chunling
INTELLIGENT SUSTAINABLE SYSTEMS, WORLDS4 2022, VOL 2, 2023, 579 : 387 - 395
[9] Developing and Pre-Processing a Dataset using a Rhetorical Relation to Build a Question-Answering System based on an Unsupervised Learning Approach
Dutta, Ashit Kumar
Sait, Abdul Rahaman Wahab
Keshta, Ismail Mohamed
Elhalles, Abheer
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2021, 21 (11): : 199 - 206

← 1 →