The BETTER Cross-Language Information Retrieval Datasets

被引:3
作者
Soboroff, Ian [1 ]
机构
[1] NIST, Gaithersburg, MD 20899 USA
来源
PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023 | 2023年
关键词
information retrieval; test collection; information extraction;
D O I
10.1145/3539618.3591910
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The IARPA BETTER (Better Extraction from Text Through Enhanced Retrieval) program held three evaluations of information retrieval (IR) and information extraction (IE). For both tasks, the only training data available was in English, but systems had to perform cross-language retrieval and extraction from Arabic, Farsi, Chinese, Russian, and Korean. Pooled assessment and information extraction annotation were used to create reusable IR test collections. These datasets are freely available to researchers working in cross-language retrieval, information extraction, or the conjunction of IR and IE. This paper describes the datasets, how they were constructed, and how they might be used by researchers.
引用
收藏
页码:3047 / 3053
页数:7
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