Squib A Novel Alignment-based Approach for PARSEVAL Measures

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A4PXQGLBY" target="_blank" >RIV/00216208:11320/25:4PXQGLBY - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206613279&doi=10.1162%2fcoli_a_00512&partnerID=40&md5=abc09a1435800cf5ee3acce110723316" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206613279&doi=10.1162%2fcoli_a_00512&partnerID=40&md5=abc09a1435800cf5ee3acce110723316</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1162/coli_a_00512" target="_blank" >10.1162/coli_a_00512</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Squib A Novel Alignment-based Approach for PARSEVAL Measures

Popis výsledku v původním jazyce

We propose a novel method for calculating PARSEVAL measures to evaluate constituent parsing results. Previous constituent parsing evaluation techniques were constrained by the requirement for consistent sentence boundaries and tokenization results, proving to be stringent and inconvenient. Our new approach handles constituent parsing results obtained from raw text, even when sentence boundaries and tokenization differ from the preprocessed gold sentence. Implementing this measure is our evaluation by alignment approach. The algorithm enables the alignment of tokens and sentences in the gold and system parse trees. Our proposed algorithm draws on the analogy of sentence and word alignment commonly used in machine translation (MT). To demonstrate the intricacy of calculations and clarify any integration of configurations, we explain the implementations in detailed pseudo-code and provide empirical proof for how sentence and word alignment can improve evaluation reliability. © 2024 Association for Computational Linguistics.

Název v anglickém jazyce

Squib A Novel Alignment-based Approach for PARSEVAL Measures

Popis výsledku anglicky

We propose a novel method for calculating PARSEVAL measures to evaluate constituent parsing results. Previous constituent parsing evaluation techniques were constrained by the requirement for consistent sentence boundaries and tokenization results, proving to be stringent and inconvenient. Our new approach handles constituent parsing results obtained from raw text, even when sentence boundaries and tokenization differ from the preprocessed gold sentence. Implementing this measure is our evaluation by alignment approach. The algorithm enables the alignment of tokens and sentences in the gold and system parse trees. Our proposed algorithm draws on the analogy of sentence and word alignment commonly used in machine translation (MT). To demonstrate the intricacy of calculations and clarify any integration of configurations, we explain the implementations in detailed pseudo-code and provide empirical proof for how sentence and word alignment can improve evaluation reliability. © 2024 Association for Computational Linguistics.

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

Computational Linguistics

ISSN

0891-2017

e-ISSN

—

Svazek periodika

50

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

1181-1190

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85206613279