Commonsense LocatedNear Relation Extraction
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LocatedNear relation describes two typically co-located objects, which is a type of useful commonsense knowledge for computer vision, natural language understanding, machine comprehension, etc. We propose to automatically extract such relationship through a sentence-level classifier and aggregating the scores of entity pairs detected from a large number of sentences. To enable the research of these tasks, we release two benchmark datasets, one containing 5,000 sentences annotated with whether a mentioned entity pair has LocatedNear relation in the given sentence or not; the other containing 500 pairs of physical objects and whether they are commonly located nearby. We also propose some baseline methods for the tasks and compare the results with a state-of-the-art general-purpose relation classifier.
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