2022 EMNLP EMNLP 2022

A Gamified Approach to Frame Semantic Role Labeling

Abstract

AbstractMuch research has investigated the possibility of creating games with a purpose (GWAPs), i.e., online games whose purpose is gathering information to address the insufficient amount of data for training and testing of large language models (Von Ahn and Dabbish, 2008). Based on such work, this paper reports on the development of a game for frame semantic role labeling, where players have fun while using semantic frames as prompts for short story writing. This game will generate more annotations for FrameNet and original content for annotation, supporting FrameNet’s goal of characterizing the English language in terms of Frame Semantics.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Interdisciplinary and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — frame semantic role labeling
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio