Exploiting Definitions for Frame Identification
Tianyu Jiang, Ellen Riloff · 2021
Frame identification is one of the key challenges for frame-semantic parsing.The goal of this task is to determine which frame best captures the meaning of a target word or phrase in a sentence.We present a new model for frame identification that uses a pre-trained transformer model to generate representations for frames and lexical units (senses) using their formal definitions in FrameNet.Our frame identification model assesses the suitability of a frame for a target word in a sentence based on the semantic coherence of their meanings.We evaluate our model on three data sets and show that it consistently achieves better performance than previous systems.