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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 14 of 14 1 Predicting lexical complexity in English texts: the Complex 2.0 dataset Shardlow, Matthew; Evans, Richard; Zampieri, Marcos. - : Springer, 2022 Abstract: © 2022 The Authors. Published by Springer. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1007/s10579-022-09588-2 ; Identifying words which may cause difficulty for a reader is an essential step in most lexical text simplification systems prior to lexical substitution and can also be used for assessing the readability of a text. This task is commonly referred to as complex word identification (CWI) and is often modelled as a supervised classification problem. For training such systems, annotated datasets in which words and sometimes multi-word expressions are labelled regarding complexity are required. In this paper we analyze previous work carried out in this task and investigate the properties of CWI datasets for English. We develop a protocol for the annotation of lexical complexity and use this to annotate a new dataset, CompLex 2.0. We present experiments using both new and old datasets to investigate the nature of lexical complexity. We found that a Likert-scale annotation protocol provides an objective setting that is superior for identifying the complexity of words compared to a binary annotation protocol. We release a new dataset using our new protocol to promote the task of Lexical Complexity Prediction. Keyword: complex word identification; lexical complexity; text simplification URL: https://doi.org/10.1007/s10579-022-09588-2 http://hdl.handle.net/2436/624697 BASE Hide details 2 Investigating Text Simplification Evaluation ... Vásquez-Rodríguez, Laura; Shardlow, Matthew; Przybyła, Piotr. - : arXiv, 2021 BASE Show details 3 Investigating Text Simplification Evaluation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Ananiadou, Sophia; Przybyła, Piotr. - : Underline Science Inc., 2021 BASE Show details 4 Predicting Lexical Complexity in English Texts ... Shardlow, Matthew; Evans, Richard; Zampieri, Marcos. - : arXiv, 2021 BASE Show details 5 SemEval-2021 Task 1: Lexical Complexity Prediction ... Shardlow, Matthew; Evans, Richard; Paetzold, Gustavo Henrique. - : arXiv, 2021 BASE Show details 6 SemEval-2021 Task 1: Lexical Complexity Prediction ... Shardlow, Matthew; Evans, Richard; Paetzold, Gustavo. - : Zenodo, 2021 BASE Show details 7 SemEval-2021 Task 1: Lexical Complexity Prediction ... Shardlow, Matthew; Evans, Richard; Paetzold, Gustavo. - : Zenodo, 2021 BASE Show details 8 SemEval-2021 Task 1: Lexical Complexity Prediction ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Evans, Richard; Paetzold, Gustavo. - : Underline Science Inc., 2021 BASE Show details 9 SemEval-2021 task 1: Lexical complexity prediction Evans, Richard; Zampieri, Marcos; Shardlow, Matthew. - : Association for Computational Linguistics, 2021 BASE Show details 10 CompLex: A New Corpus for Lexical Complexity Prediction from Likert Scale Data ... Shardlow, Matthew; Cooper, Michael; Zampieri, Marcos. - : arXiv, 2020 BASE Show details 11 Detecting Multiword Expression Type Helps Lexical Complexity Assessment ... Kochmar, Ekaterina; Gooding, Sian; Shardlow, Matthew. - : arXiv, 2020 BASE Show details 12 Multi-Word Lexical Simplification ... The 28th International Conference on Computational Linguistics 2020; Przybyła, Piotr; Shardlow, Matthew. - : Underline Science Inc., 2020 BASE Show details 13 Identification of research hypotheses and new knowledge from scientific literature ... Shardlow, Matthew; Batista-Navarro, Riza; Thompson, Paul. - : Figshare, 2018 BASE Show details 14 Identification of research hypotheses and new knowledge from scientific literature ... Shardlow, Matthew; Batista-Navarro, Riza; Thompson, Paul. - : Figshare, 2018 BASE Show details

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