activity
20172026
most citedHow compatible are our discourse annotations? Insights from mapping RST-DT and PDTB annotations

6 citations · 6 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2026

Human Label Variation in Implicit Discourse Relation Recognition

Frances Yung, Daniil Ignatev, Merel Scholman +2

There is growing recognition that many NLP tasks lack a single ground truth, as human judgments reflect diverse perspectives. To capture this variation, models have been developed…

cs.CL2025

Synthetic Data Augmentation for Cross-domain Implicit Discourse Relation Recognition

Frances Yung, Varsha Suresh, Zaynab Reza +2

Implicit discourse relation recognition (IDRR) -- the task of identifying the implicit coherence relation between two text spans -- requires deep semantic understanding. Recent stu…

cs.CL2024

On Crowdsourcing Task Design for Discourse Relation Annotation

Frances Yung, Vera Demberg

Interpreting implicit discourse relations involves complex reasoning, requiring the integration of semantic cues with background knowledge, as overt connectives like because or the…

cs.CL2024

Implicit Discourse Relation Classification For Nigerian Pidgin

Muhammed Saeed, Peter Bourgonje, Vera Demberg

Despite attempts to make Large Language Models multi-lingual, many of the world's languages are still severely under-resourced. This widens the performance gap between NLP and AI a…

cs.CL2024

Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgin

Pin-Jie Lin, Merel Scholman, Muhammed Saeed +1

Nigerian Pidgin is an English-derived contact language and is traditionally an oral language, spoken by approximately 100 million people. No orthographic standard has yet been adop…

cs.CL2024

Prompting Implicit Discourse Relation Annotation

Frances Yung, Mansoor Ahmad, Merel Scholman +1

Pre-trained large language models, such as ChatGPT, archive outstanding performance in various reasoning tasks without supervised training and were found to have outperformed crowd…

cs.CL2023

Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design

Valentina Pyatkin, Frances Yung, Merel C. J. Scholman +3

Disagreement in natural language annotation has mostly been studied from a perspective of biases introduced by the annotators and the annotation frameworks. Here, we propose to ana…

cs.CL2017★ 6 cited

How compatible are our discourse annotations? Insights from mapping RST-DT and PDTB annotations

Vera Demberg, Fatemeh Torabi Asr, Merel Scholman

Discourse-annotated corpora are an important resource for the community, but they are often annotated according to different frameworks. This makes comparison of the annotations di…