@inproceedings{pais-etal-2020-processing,
title = "A Processing Platform Relating Data and Tools for {R}omanian Language",
author = "P{\u{a}}i{\textcommabelow{s}}, Vasile and
Ion, Radu and
Tufi{\textcommabelow{s}}, Dan",
editor = "Rehm, Georg and
Bontcheva, Kalina and
Choukri, Khalid and
Haji{\v{c}}, Jan and
Piperidis, Stelios and
Vasi{\c{l}}jevs, Andrejs",
booktitle = "Proceedings of the 1st International Workshop on Language Technology Platforms",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.iwltp-1.13",
pages = "81--88",
abstract = "This paper presents RELATE (\url{http://relate.racai.ro}), a high-performance natural language platform designed for Romanian language. It is meant both for demonstration of available services, from text-span annotations to syntactic dependency trees as well as playing or automatically synthesizing Romanian words, and for the development of new annotated corpora. It also incorporates the search engines for the large COROLA reference corpus of contemporary Romanian and the Romanian wordnet. It integrates multiple text and speech processing modules and exposes their functionality through a web interface designed for the linguist researcher. It makes use of a scheduler-runner architecture, allowing processing to be distributed across multiple computing nodes. A series of input/output converters allows large corpora to be loaded, processed and exported according to user preferences.",
language = "English",
ISBN = "979-10-95546-64-1",
}
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<abstract>This paper presents RELATE (http://relate.racai.ro), a high-performance natural language platform designed for Romanian language. It is meant both for demonstration of available services, from text-span annotations to syntactic dependency trees as well as playing or automatically synthesizing Romanian words, and for the development of new annotated corpora. It also incorporates the search engines for the large COROLA reference corpus of contemporary Romanian and the Romanian wordnet. It integrates multiple text and speech processing modules and exposes their functionality through a web interface designed for the linguist researcher. It makes use of a scheduler-runner architecture, allowing processing to be distributed across multiple computing nodes. A series of input/output converters allows large corpora to be loaded, processed and exported according to user preferences.</abstract>
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%0 Conference Proceedings
%T A Processing Platform Relating Data and Tools for Romanian Language
%A Păi\textcommabelows, Vasile
%A Ion, Radu
%A Tufi\textcommabelows, Dan
%Y Rehm, Georg
%Y Bontcheva, Kalina
%Y Choukri, Khalid
%Y Hajič, Jan
%Y Piperidis, Stelios
%Y Vasiļjevs, Andrejs
%S Proceedings of the 1st International Workshop on Language Technology Platforms
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-64-1
%G English
%F pais-etal-2020-processing
%X This paper presents RELATE (http://relate.racai.ro), a high-performance natural language platform designed for Romanian language. It is meant both for demonstration of available services, from text-span annotations to syntactic dependency trees as well as playing or automatically synthesizing Romanian words, and for the development of new annotated corpora. It also incorporates the search engines for the large COROLA reference corpus of contemporary Romanian and the Romanian wordnet. It integrates multiple text and speech processing modules and exposes their functionality through a web interface designed for the linguist researcher. It makes use of a scheduler-runner architecture, allowing processing to be distributed across multiple computing nodes. A series of input/output converters allows large corpora to be loaded, processed and exported according to user preferences.
%U https://aclanthology.org/2020.iwltp-1.13
%P 81-88
Markdown (Informal)
[A Processing Platform Relating Data and Tools for Romanian Language](https://aclanthology.org/2020.iwltp-1.13) (Păiș et al., IWLTP 2020)
ACL