Uniform Meaning Representation 2.0
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10513459" target="_blank" >RIV/00216208:11320/25:10513459 - isvavai.cz</a>
Výsledek na webu
<a href="http://hdl.handle.net/11234/1-5902" target="_blank" >http://hdl.handle.net/11234/1-5902</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Uniform Meaning Representation 2.0
Popis výsledku v původním jazyce
The goal of the Uniform Meaning Representation (UMR) project is to design a meaning representation that can be used to annotate the semantic content of a text. UMR is primarily based on Abstract Meaning Representation (AMR), an annotation framework initially designed for English, but also draws from other meaning representations. UMR extends AMR to other languages, particularly morphologically complex, low-resource languages. UMR also adds features to AMR that are critical to semantic interpretation and enhances AMR by proposing a companion document-level representation that captures linguistic phenomena such as coreference as well as temporal and modal dependencies that potentially go beyond sentence boundaries. UMR is intended to be scalable, learnable, and cross-linguistically plausible. It is designed to support both lexical and logical inference.
Název v anglickém jazyce
Uniform Meaning Representation 2.0
Popis výsledku anglicky
The goal of the Uniform Meaning Representation (UMR) project is to design a meaning representation that can be used to annotate the semantic content of a text. UMR is primarily based on Abstract Meaning Representation (AMR), an annotation framework initially designed for English, but also draws from other meaning representations. UMR extends AMR to other languages, particularly morphologically complex, low-resource languages. UMR also adds features to AMR that are critical to semantic interpretation and enhances AMR by proposing a companion document-level representation that captures linguistic phenomena such as coreference as well as temporal and modal dependencies that potentially go beyond sentence boundaries. UMR is intended to be scalable, learnable, and cross-linguistically plausible. It is designed to support both lexical and logical inference.
Klasifikace
Druh
X - Nezařazeno
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů