@inproceedings{schacht-delucchi-danhier-2025-explay,
title = "{E}xp{L}ay: A new Corpus Resource for the Research on Expertise as an Influential Factor on Language Production",
author = "Schacht, Carmen and
Delucchi Danhier, Renate",
editor = "Peng, Siyao and
Rehbein, Ines",
booktitle = "Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.law-1.17/",
doi = "10.18653/v1/2025.law-1.17",
pages = "216--227",
ISBN = "979-8-89176-262-6",
abstract = "This paper introduces the ExpLay-Pipeline, a novel semi-automated processing tool designed for the analysis of language production data from experts in comparison to the language production of a control group of laypeople. The pipeline combines manual annotation and curation with state-of-the-art machine learning and rule-based methods, following a silver standard approach. It integrates various analysis modules specifically for the syntactic and lexical evaluation of parsed linguistic data. While implemented initially for the creation of the ExpLay-Corpus, it is designed for the processing of linguistic data in general. The paper details the design and implementation of this pipeline."
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%0 Conference Proceedings
%T ExpLay: A new Corpus Resource for the Research on Expertise as an Influential Factor on Language Production
%A Schacht, Carmen
%A Delucchi Danhier, Renate
%Y Peng, Siyao
%Y Rehbein, Ines
%S Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-262-6
%F schacht-delucchi-danhier-2025-explay
%X This paper introduces the ExpLay-Pipeline, a novel semi-automated processing tool designed for the analysis of language production data from experts in comparison to the language production of a control group of laypeople. The pipeline combines manual annotation and curation with state-of-the-art machine learning and rule-based methods, following a silver standard approach. It integrates various analysis modules specifically for the syntactic and lexical evaluation of parsed linguistic data. While implemented initially for the creation of the ExpLay-Corpus, it is designed for the processing of linguistic data in general. The paper details the design and implementation of this pipeline.
%R 10.18653/v1/2025.law-1.17
%U https://aclanthology.org/2025.law-1.17/
%U https://doi.org/10.18653/v1/2025.law-1.17
%P 216-227
Markdown (Informal)
[ExpLay: A new Corpus Resource for the Research on Expertise as an Influential Factor on Language Production](https://aclanthology.org/2025.law-1.17/) (Schacht & Delucchi Danhier, LAW 2025)
ACL