ding-01 :ARG0: An AMR Corpus for Spontaneous French Dialogue

TL;DR

This paper introduces a French AMR corpus based on spontaneous dialogue, extending existing frameworks to better capture speech dynamics, and evaluates a parser to assist annotation.

Contribution

It presents a new French AMR corpus with tailored extensions for spontaneous speech and provides an initial parser model to aid annotation efforts.

Findings

Extended AMR framework for French spontaneous speech

Published a freely available annotated corpus

Developed an initial parser model for annotation assistance

Abstract

We present our work to build a French semantic corpus by annotating French dialogue in Abstract Meaning Representation (AMR). Specifically, we annotate the DinG corpus, consisting of transcripts of spontaneous French dialogues recorded during the board game Catan. As AMR has insufficient coverage of the dynamics of spontaneous speech, we extend the framework to better represent spontaneous speech and sentence structures specific to French. Additionally, to support consistent annotation, we provide an annotation guideline detailing these extensions. We publish our corpus under a free license (CC-SA-BY). We also train and evaluate an AMR parser on our data. This model can be used as an assistance annotation tool to provide initial annotations that can be refined by human annotators. Our work contributes to the development of semantic resources for French dialogue.