DeModify: A Dataset for Analyzing Contextual Constraints on Modifier Deletion

Abstract

Tasks such as knowledge extraction, text simplification and summarization have in common the fact that from a text fragment a smaller (not necessarily contiguous) portion is obtained by discarding part of the context. This may cause the text fragment to acquire a new meaning, or even to become false. The smallest units that can be considered disposable in a larger context are modifiers. In this paper we describe a dataset collected and annotated to facilitate the study of the influence of modifiers on the meaning of the context they are part of, and to support the development of models that can determine whether a modifier can be removed without undesirable semantic consequences.

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