Shall We Trust All Relational Tuples by Open Information Extraction? A
  Study on Speculation Detection
Kuicai Dong Aixin Sun Jung-Jae Kim Xiaoli Li
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.