Dr. Merel Scholman
Assistant Professor
Publications
2023
Scholarly publications
Sanders, T., Hoek, J., & Scholman, M. (2023). Experimental methods in discourse studies. In The Routledge Handbook of Experimental Linguistics (pp. 120-138). Routledge. https://merelscholman.github.io/.github.io/authorcopies/Sandersetal2023_authorcopy.pdf
Pyatkin, V., Yung, F., Scholman, M. C. J., Tsarfaty, R., Dagan, I., & Demberg, V. (2023). Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design. Transactions of the Association for Computational Linguistics, 11, 1014-1032. https://doi.org/10.1162/tacl_a_00586
Marchal, M., Scholman, M. C. J., & Demberg, V. (2023). How statistical correlations influence discourse-level processing: Clause type as a cue for discourse relations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 1-12. https://doi.org/10.1037/xlm0001270
Lin, P-J., Saeed, M., Chang, E., & Scholman, M. (2023). Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin. In Proceedings of the 24th INTERSPEECH conference (pp. 3954-3958)
Hoek, J., & Scholman, M. (2023). Expressing non-volitional causality in English. In Micro- and Marcro-variation of Causal Clauses. Synchronic and Diachronic Insights (pp. 167–183). John Benjamins.
2022
Scholarly publications
Yung, F., Anuranjana, K., Scholman, M., & Demberg, V. (2022). Label distributions help implicit discourse relation classification. In Proceedings of the Third Workshop on Computational Approaches to Discourse (CODI)
Scholman, M., Pyatkin, V., Yung, F., Dagan, I., Tsarfaty, R., & Demberg, V. (2022). Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training. In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 22)
Scholman, M., Dong, T., Yung, F., & Demberg, V. (2022). DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations. In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 22)
Marchal, M., Scholman, M., Yung, F., & Demberg, V. (2022). Establishing annotation quality in multi-label annotations. In Proceedings of the 29th International Conference on Computational Linguistic (COLING) (pp. 3659–3668)
Scholman, M., Demberg, V., & Sanders, T. J. M. (2022). Descriptively adequate and cognitively plausible? Validating distinctions between types of coherence relations. Discours, 30, 1-33. https://doi.org/10.4000/discours.12075
Scholman, M. C. J., Blything, L., Cain, K., Hoek, J., & Evers-Vermeul, J. (2022). Discourse rules: The effects of clause order principles on the reading process. Language, Cognition and Neuroscience, 37(10), 1277-1291. https://doi.org/10.1080/23273798.2022.2077971
Marchal, M., Scholman, M. C. J., & Demberg, V. (2022). The effect of domain knowledge on discourse relation inferences: Relation marking and interpretation strategies. Dialogue and Discourse, 13(2), 49-78. https://doi.org/10.5210/dad.2022.202
2021
Scholarly publications
Hoek, J., Scholman, M., & Sanders, T. (2021). Is there less agreement when the discourse is underspecified? Annotation of coherence relations in TED talks. In Proceedings of the First Workshop on Integrating Perspectives on Discourse Annotation (pp. 1–6). Association for Computational Linguistics (ACL).
Marchal, M., Scholman, M., & Demberg, V. (2021). Semi-automatic discourse annotation in a low-resource language: Developing a connective lexicon for Nigerian Pidgin. In 2nd Workshop on Computational Approaches to Discourse, CODI 2021 - Proceedings of the Workshop
Scholman, M. C. J., Dong, T., Yung, F., & Demberg, V. (2021). Comparison of methods for explicit discourse connective identification across various domains. In 2nd Workshop on Computational Approaches to Discourse, CODI 2021 - Proceedings of the Workshop
Yung, F., Scholman, M. C. J., & Demberg, V. (2021). A practical perspective on connective generation. In 2nd Workshop on Computational Approaches to Discourse, CODI 2021 - Proceedings of the Workshop
Sanders, T. J. M., Demberg, V., Hoek, J., Scholman, M. C. J., Scholman, M., Asr, F. T., Zufferey, S., & Evers-Vermeul, J. (2021). Unifying dimensions in coherence relations: How various annotation frameworks are related. Corpus linguistics and Linguistic theory, 17(1), 1-71. Advance online publication. https://doi.org/10.1515/cllt-2016-0078
2020
Scholarly publications
Scholman, M., Demberg, V., & Sanders, T. J. M. (2020). Individual differences in expecting coherence relations: Exploring the variability in sensitivity to contextual signals in discourse. Discourse Processes, 57(10), 844-861. https://doi.org/10.1080/0163853X.2020.1813492
2019
Scholarly publications
Scholman, M. (2019). Coherence relations in discourse and cognition: Mapping approaches, annotations, and interpretations. [Doctoral thesis 3 (Research UU / Graduation NOT UU), Saarland University].
Demberg, V., Scholman, M. C. J., & Asr, F. T. (2019). How compatible are our discourse annotation frameworks? Insights from mapping RST-DT and PDTB annotations. Dialogue and Discourse, 10(1), 87-135. https://doi.org/10.5087/dad.2019.104
Yung, F., Scholman, M. C. J., & Demberg, V. (2019). Crowdsourcing discourse relation annotations by a two-step connective insertion task. In LAW 2019 - 13th Linguistic Annotation Workshop, Proceedings of the Workshop (pp. 16-25). (LAW 2019 - 13th Linguistic Annotation Workshop, Proceedings of the Workshop). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w19-4003
2017
Scholarly publications
Scholman, M. C. J., & Demberg, V. (2017). Crowdsourcing discourse interpretations: On the influence of context and the reliability of a connective insertion task. In LAW 2017 - 11th Linguistic Annotation Workshop, Proceedings of the Workshop (pp. 24-33). (LAW 2017 - 11th Linguistic Annotation Workshop, Proceedings of the Workshop). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-0803
Scholman, M. C. J., & Demberg, V. (2017). Examples and specifications that prove a point: Identifying elaborative and argumentative discourse relations. Dialogue and Discourse, 8(2), 56-83. https://doi.org/10.5087/dad.2017.203
Scholman, M. C. J., Rohde, H., & Demberg, V. (2017). “On the one hand” as a cue to anticipate upcoming discourse structure. Journal of Memory and Language, 97, 47-60. https://doi.org/10.1016/j.jml.2017.07.010
Hoek, J., & Scholman, M. (2017). Evaluating discourse annotation: Some recent insights and new approaches. In Proceedings 13th Joint ISO - ACL Workshop on Interoperable Semantic Annotation (isa-13) (pp. 1-13)
https://dspace.library.uu.nl/bitstream/handle/1874/356053/ISA13.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/356053/ISA13.pdf?sequence=1
Evers-Vermeul, J., Hoek, J., & Scholman, M. (2017). On temporality in discourse annotation: Theoretical and practical considerations. Dialogue & DIscourse, 8(2), 1-20. https://doi.org/10.5087/dad.2017.201
https://dspace.library.uu.nl/bitstream/handle/1874/355961/9.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/355961/9.pdf?sequence=1
2016
Scholarly publications
Rehbein, I., Scholman, M., & Demberg, V. (2016). Annotating discourse relations in spoken language: A comparison of the PDTB and CCR frameworks. In Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016 (pp. 1039-1046). (Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016). European Language Resources Association (ELRA).
Scholman, M., Evers-Vermeul, J., & Sanders, T. J. M. (2016). A step-wise approach to discourse annotation: Towards a reliable categorization of coherence relations. Dialogue & DIscourse, 7(2), 1-28. https://doi.org/10.5087/dad.2016.201