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Merel C. J. Scholman
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- affiliation: Saarland University, Germany
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2020 – today
- 2024
- [c11]Frances Yung, Merel C. J. Scholman, Sárka Zikánová, Vera Demberg:
DiscoGeM 2.0: A Parallel Corpus of English, German, French and Czech Implicit Discourse Relations. LREC/COLING 2024: 4940-4956 - [c10]Pin-Jie Lin, Merel C. J. Scholman, Muhammed Saeed, Vera Demberg:
Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgin. LREC/COLING 2024: 11510-11522 - [c9]Schuyler Laparle, Gaëlle Ferré, Merel C. J. Scholman:
More Than One Gesture but Less Than Two? Inter-stroke Dependencies in Form and Meaning. HCI (28) 2024: 245-264 - [i5]Frances Yung, Mansoor Ahmad, Merel C. J. Scholman, Vera Demberg:
Prompting Implicit Discourse Relation Annotation. CoRR abs/2402.04918 (2024) - [i4]Pin-Jie Lin, Merel C. J. Scholman, Muhammed Saeed, Vera Demberg:
Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgin. CoRR abs/2404.18264 (2024) - 2023
- [j5]Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, Reut Tsarfaty, Ido Dagan, Vera Demberg:
Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design. Trans. Assoc. Comput. Linguistics 11: 1014-1032 (2023) - [c8]Pin-Jie Lin, Muhammed Saeed, Ernie Chang, Merel C. J. Scholman:
Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin. INTERSPEECH 2023: 3954-3958 - [c7]Frances Yung, Merel C. J. Scholman, Ekaterina Lapshinova-Koltunski, Christina Pollkläsener, Vera Demberg:
Investigating Explicitation of Discourse Connectives in Translation using Automatic Annotations. SIGDIAL 2023: 21-30 - [i3]Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, Reut Tsarfaty, Ido Dagan, Vera Demberg:
Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design. CoRR abs/2304.00815 (2023) - [i2]Pin-Jie Lin, Muhammed Saeed, Ernie Chang, Merel C. J. Scholman:
Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin. CoRR abs/2307.00382 (2023) - 2022
- [j4]Marian Marchal, Merel C. J. Scholman, Vera Demberg:
The effect of domain knowledge and implicitation on discourse relation inferences. Dialogue Discourse 13(2): 49-78 (2022) - [c6]Marian Marchal, Merel C. J. Scholman, Frances Yung, Vera Demberg:
Establishing Annotation Quality in Multi-label Annotations. COLING 2022: 3659-3668 - [c5]Merel C. J. Scholman, Valentina Pyatkin, Frances Yung, Ido Dagan, Reut Tsarfaty, Vera Demberg:
Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training. LREC 2022: 2148-2156 - [c4]Merel C. J. Scholman, Tianai Dong, Frances Yung, Vera Demberg:
DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations. LREC 2022: 3281-3290
2010 – 2019
- 2019
- [c3]Frances Yung, Vera Demberg, Merel C. J. Scholman:
Crowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task. LAW@ACL 2019: 16-25 - 2017
- [j3]Jacqueline Evers-Vermeul, Jet Hoek, Merel C. J. Scholman:
On Temporality in Discourse Annotation: Theoretical and Practical Considerations. Dialogue Discourse 8(2): 1-20 (2017) - [j2]Merel C. J. Scholman, Vera Demberg:
Examples and Specifications that Prove a Point: Identifying Elaborative and Argumentative Discourse Relations. Dialogue Discourse 8(2): 56-83 (2017) - [c2]Merel C. J. Scholman, Vera Demberg:
Crowdsourcing discourse interpretations: On the influence of context and the reliability of a connective insertion task. LAW@ACL 2017: 24-33 - [i1]Vera Demberg, Fatemeh Torabi Asr, Merel C. J. Scholman:
How consistent are our discourse annotations? Insights from mapping RST-DT and PDTB annotations. CoRR abs/1704.08893 (2017) - 2016
- [j1]Merel C. J. Scholman, Jacqueline Evers-Vermeul, Ted Sanders:
Categories of coherence relations in discourse annotation. Dialogue Discourse 7(2): 1-28 (2016) - [c1]Ines Rehbein, Merel C. J. Scholman, Vera Demberg:
Annotating Discourse Relations in Spoken Language: A Comparison of the PDTB and CCR Frameworks. LREC 2016
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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