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Shall We Trust All Relational Tuples by Open Information Extraction? A Study on Speculation Detection

Authors :
Dong, Kuicai
Sun, Aixin
Kim, Jung-Jae
Li, Xiaoli
Publication Year :
2023

Abstract

Open Information Extraction (OIE) aims to extract factual relational tuples from open-domain sentences. Downstream tasks use the extracted OIE tuples as facts, without examining the certainty of these facts. However, uncertainty/speculation is a common linguistic phenomenon. Existing studies on speculation detection are defined at sentence level, but even if a sentence is determined to be speculative, not all tuples extracted from it may be speculative. In this paper, we propose to study speculations in OIE and aim to determine whether an extracted tuple is speculative. We formally define the research problem of tuple-level speculation detection and conduct a detailed data analysis on the LSOIE dataset which contains labels for speculative tuples. Lastly, we propose a baseline model OIE-Spec for this new research task.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2305.04181
Document Type :
Working Paper