Why is this language complex? Cherry-pick the optimal set of features in multilingual treebanks

Author:

Brunato Dominique1,Venturi Giulia1

Affiliation:

1. Institute for Computational Linguistics ”A. Zampolli” (ILC-CNR) - ItaliaNLP Lab , Pisa , Italy

Abstract

Abstract This paper investigates linguistic complexity across natural languages from a corpus-based perspective and relies on the assumptions of linguistic profiling as a methodological framework. We focus in particular on the domain of syntactic complexity and analyze the distribution of a set of features taken as proxies of complexity phenomena at sentence level, which were extracted from 63 treebanks annotated according to the Universal Dependencies formalism. This dataset guarantees that the features considered are modeling the same linguistic phenomena in different treebanks, allowing reliable comparison among languages. We show that our approach is able to identify tendencies of structural proximity between languages not necessarily in line with typologically-supported classification, thus shedding light on new corpus-based findings.

Publisher

Walter de Gruyter GmbH

Subject

Linguistics and Language,Language and Linguistics

Reference37 articles.

1. Argamon, Shlomo, Moshe Koppel, Jonathan Fine & Anat Rachel Shimoni. 2003. Gender, genre, and writing style in formal written texts. Text 23(3). 321–346. https://doi.org/10.1515/text.2003.014.

2. Berdicevskis, Aleksandrs, Çağrı Çöltekin, Katharina Ehret, Kilu von Prince, Daniel Ross, Bill Thompson, Chunxiao Yan, Vera Demberg, Gary Lupyan, Taraka Rama & Christian Bentz. 2018. Using Universal Dependencies in cross-linguistic complexity research. In Proceedings of the second workshop on universal dependencies (UDW 2018), 8–17. Brussels, Belgium: Association for Computational Linguistics.

3. Bickel, Balthasar. 2015. Distributional typology: Statistical inquiries into the dynamics linguistic diversity. In Bernd Heine & Heiko Narrog (eds.), The oxford handbook linguistic analysis. Oxford: Oxford University Press.

4. Bott, Stefan & Horacio Saggion. 2014. Text simplification resources for Spanish. Language Resources and Evaluation 48(1). 93–120. https://doi.org/10.1007/s10579-014-9265-4.

5. Brunato, Dominique, Andrea Cimino, Felice Dell’Orletta, Giulia Venturi & Simonetta Montemagni. 2020. Profiling-UD: A tool for linguistic profiling of texts. English. In Proceedings of the 12th language resources and evaluation conference, 7145–7151. Marseille, France: European Language Resources Association.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3