PAMR: Persian Abstract Meaning Representation Corpus

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AMKAGXKUC" target="_blank" >RIV/00216208:11320/25:MKAGXKUC - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188280597&doi=10.1145%2f3638288&partnerID=40&md5=45e8e4d2993601eebb1bb18cc5a2cac1" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188280597&doi=10.1145%2f3638288&partnerID=40&md5=45e8e4d2993601eebb1bb18cc5a2cac1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3638288" target="_blank" >10.1145/3638288</a>

Jazyk výsledku

angličtina

Název v původním jazyce

PAMR: Persian Abstract Meaning Representation Corpus

Popis výsledku v původním jazyce

One of the most used and well-known semantic representation models is Abstract Meaning Representation (AMR). This representation has had numerous applications in natural language processing tasks in recent years. Currently, for English and Chinese languages, large annotated corpora are available. In addition, in some low-resource languages, related corpora have been generated with less size; although, until now, to the best of our knowledge, there is not any AMR corpus for the Persian/Farsi language. Therefore, the aim of this article is to create a Persian AMR (PAMR) corpus via translating English sentences and adjusting AMR guidelines and to solve the various challenges that are faced in this regard. The result of this research is a corpus, containing 1,020 Persian sentences and their related AMR that can be used in various natural language processing tasks. In this article, to investigate the feasibility of using the corpus, we have applied it to two natural language processing tasks: Sentiment Analysis and Text Summarization. © 2024 Copyright held by the owner/author(s).

Název v anglickém jazyce

PAMR: Persian Abstract Meaning Representation Corpus

Popis výsledku anglicky

One of the most used and well-known semantic representation models is Abstract Meaning Representation (AMR). This representation has had numerous applications in natural language processing tasks in recent years. Currently, for English and Chinese languages, large annotated corpora are available. In addition, in some low-resource languages, related corpora have been generated with less size; although, until now, to the best of our knowledge, there is not any AMR corpus for the Persian/Farsi language. Therefore, the aim of this article is to create a Persian AMR (PAMR) corpus via translating English sentences and adjusting AMR guidelines and to solve the various challenges that are faced in this regard. The result of this research is a corpus, containing 1,020 Persian sentences and their related AMR that can be used in various natural language processing tasks. In this article, to investigate the feasibility of using the corpus, we have applied it to two natural language processing tasks: Sentiment Analysis and Text Summarization. © 2024 Copyright held by the owner/author(s).

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

ACM Transactions on Asian and Low-Resource Language Information Processing

ISSN

2375-4699

e-ISSN

—

Svazek periodika

23

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

20

Strana od-do

1-20

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85188280597