The Temporal Game: A New Perspective on Temporal Relation Extraction
This work addresses the problem of temporal annotation for researchers and practitioners in natural language processing by offering a novel interactive tool, though it appears incremental as it builds on existing temporal reasoning concepts.
The paper tackles temporal relation extraction by introducing the Temporal Game, which decomposes interval-level relations into point-wise comparisons and uses temporal closure for consistency, enabling more fine-grained annotation and supporting both interval and instant entities. It presents a demo with Game and Annotation modes for the TempEval-3 dataset and custom documents, available publicly with open-source code.
In this paper we demo the Temporal Game, a novel approach to temporal relation extraction that casts the task as an interactive game. Instead of directly annotating interval-level relations, our approach decomposes them into point-wise comparisons between the start and end points of temporal entities. At each step, players classify a single point relation, and the system applies temporal closure to infer additional relations and enforce consistency. This point-based strategy naturally supports both interval and instant entities, enabling more fine-grained and flexible annotation than any previous approach. The Temporal Game also lays the groundwork for training reinforcement learning agents, by treating temporal annotation as a sequential decision-making task. To showcase this potential, the demo presented in this paper includes a Game mode, in which users annotate texts from the TempEval-3 dataset and receive feedback based on a scoring system, and an Annotation mode, that allows custom documents to be annotated and resulting timeline to be exported. Therefore, this demo serves both as a research tool and an annotation interface. The demo is publicly available at https://temporal-game.inesctec.pt, and the source code is open-sourced to foster further research and community-driven development in temporal reasoning and annotation.