Methods of Solving the Problem of Coreference and Searching for Noun Phrases in Natural Languages
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3A3UGB7FF4" target="_blank" >RIV/00216208:11320/26:3UGB7FF4 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1134/S1064230725700108" target="_blank" >http://dx.doi.org/10.1134/S1064230725700108</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1134/S1064230725700108" target="_blank" >10.1134/S1064230725700108</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Methods of Solving the Problem of Coreference and Searching for Noun Phrases in Natural Languages
Popis výsledku v původním jazyce
Abstract: Coreference is a task in the field of natural language processing aimed at linking words and phrases in a text that point to the same extra-linguistic object or referent. It is applicable in text summarization, question answering, information retrieval, and dialog systems. In this paper, the existing methods for solving the coreferencing problem are dissected and a method based on the application of a two-stage machine learning model is proposed. The language model converts text tokens into vector representations. Then, for each pair of tokens, based on their vector representations, an estimate of the probability of finding these tokens either in one noun phrase or in two coreference noun phrases is computed. Thus, the method simultaneously searches for noun phrases and predicts the coreference relationship between them. © Pleiades Publishing, Ltd. 2025.
Název v anglickém jazyce
Methods of Solving the Problem of Coreference and Searching for Noun Phrases in Natural Languages
Popis výsledku anglicky
Abstract: Coreference is a task in the field of natural language processing aimed at linking words and phrases in a text that point to the same extra-linguistic object or referent. It is applicable in text summarization, question answering, information retrieval, and dialog systems. In this paper, the existing methods for solving the coreferencing problem are dissected and a method based on the application of a two-stage machine learning model is proposed. The language model converts text tokens into vector representations. Then, for each pair of tokens, based on their vector representations, an estimate of the probability of finding these tokens either in one noun phrase or in two coreference noun phrases is computed. Thus, the method simultaneously searches for noun phrases and predicts the coreference relationship between them. © Pleiades Publishing, Ltd. 2025.
Klasifikace
Druh
J<sub>SC</sub> - 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)
Návaznosti výsledku
Projekt
—
Návaznosti
—
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal of Computer and Systems Sciences International
ISSN
1064-2307
e-ISSN
—
Svazek periodika
64
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
15
Strana od-do
121-135
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-105004467498