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When Do Discourse Markers Affect Computational Sentence Understanding? by Li, Ruiqi; Allein, Liesbeth; Sileo, Damien; Moens, Marie-Francine is a scholarly article available to read on EtoBox.

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The capabilities and use cases of automatic natural language processing (NLP) have grown significantly over the last few years. While much work has been devoted to understanding how humans deal with discourse connectives, this phenomenon is understudied in computational systems. Therefore, it is important to put NLP models under the microscope and examine whether they can adequately comprehend, process, and reason within the complexity of natural language. In this chapter, we introduce the main mechanisms behind automatic sentence processing systems step by step and then focus on evaluating discourse connective processing. We assess nine popular systems in their ability to understand English discourse connectives and analyze how context and language understanding tasks affect their connective comprehension. The results show that NLP systems do not process all discourse connectives equally well and that the computational processing complexity of different connective kinds is not always consistently in line with the presumed complexity order found in human processing. In addition, while humans are more inclined to be influenced during the reading procedure but not necessarily in the

Author

Li, Ruiqi; Allein, Liesbeth; Sileo, Damien; Moens, Marie-Francine

Published

2023

Language

EN