Detecting Future-related Contexts of Entity Mentions

• URL: http://arxiv.org/abs/2502.15332v1
• Date: Fri, 21 Feb 2025 09:34:34 GMT
• Title: Detecting Future-related Contexts of Entity Mentions
• Authors: Puneet Prashar, Krishna Mohan Shukla, Adam Jatowt,
• Abstract summary: This paper focuses on detecting implicit future references in entity-centric texts.<n>We first present a novel dataset of 19,540 sentences built around popular entities sourced from Wikipedia.
• Score: 15.144785147549713
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The ability to automatically identify whether an entity is referenced in a future context can have multiple applications including decision making, planning and trend forecasting. This paper focuses on detecting implicit future references in entity-centric texts, addressing the growing need for automated temporal analysis in information processing. We first present a novel dataset of 19,540 sentences built around popular entities sourced from Wikipedia, which consists of future-related and non-future-related contexts in which those entities appear. As a second contribution, we evaluate the performance of several Language Models including also Large Language Models (LLMs) on the task of distinguishing future-oriented content in the absence of explicit temporal references.

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