SemEval-2019 Task 2: Unsupervised Lexical Frame Induction

Autor: Laura Kallmeyer, Regina Stodden, Behrang QasemiZadeh, Marie Candito, Miriam R. L. Petruck

Publikováno v: SemEval@NAACL-HLT

This paper presents Unsupervised Lexical Frame Induction, Task 2 of the International Workshop on Semantic Evaluation in 2019. Given a set of prespecified syntactic forms in context, the task requires that verbs and their arguments be clustered to re

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6ee255530a2896526a436891c1e8c442
https://doi.org/10.18653/v1/s19-2003

PARSEME multilingual corpus of verbal multiword expressions

Autor: Savary, Agata, Marie Candito, Verginica Barbu Mititelu, Eduard Bejček, Fabienne Cap, Slavomír Čéplö, Silvio Ricardo Cordeiro, Gülşen Eryiğit, Voula Giouli, Maarten van Gompel, Yaakov HaCohen-Kerner, Jolanta Kovalevskaitė, Simon Krek, Chaya Liebeskind, Johanna Monti, Carla Parra Escartín, Lonneke van der Plas, Behrang QasemiZadeh, Carlos Ramisch, Federico Sangati, Ivelina Stoyanova, Veronika Vincze

Publikováno v: Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop
Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop, 2018
BASE-Bielefeld Academic Search Engine

Multiword expressions (MWEs) are known as a “pain in the neck” due to their idiosyncratic behaviour. While some categories of MWEs have been largely stud- ied, verbal MWEs (VMWEs) such as to take a walk, to break one’s heart or to turn off have

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::154cb5e2ac0b890b2665015d5ff0a568
https://hal.archives-ouvertes.fr/hal-01917174/document

Coarse Lexical Frame Acquisition at the Syntax–Semantics Interface Using a Latent-Variable PCFG Model

Autor: Behrang QasemiZadeh, Laura Kallmeyer, Jackie Chi Kit Cheung

Publikováno v: SEM@NAACL-HLT

We present a method for unsupervised lexical frame acquisition at the syntax–semantics interface. Given a set of input strings derived from dependency parses, our method generates a set of clusters that resemble lexical frame structures. Our work i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8c437e72b9ea32c97448ca54506f9c21
https://doi.org/10.18653/v1/s18-2016

A Cross-Lingual Approach for Building Multilingual Sentiment Lexicons

Autor: Behzad Naderalvojoud, Ebru Akcapinar Sezer, Laura Kallmeyer, Behrang QasemiZadeh

Publikováno v: Text, Speech, and Dialogue ISBN: 9783030007935
TSD

We propose a cross-lingual distributional model to build sentiment lexicons in many languages from resources available in English. We evaluate this method for two languages, German and Turkish, and on several datasets. We show that the sentiment lexi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5a4b12d0bdfa1238044912b9352c5f2
https://doi.org/10.1007/978-3-030-00794-2_28

SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers

Autor: Thierry Charnois, Behrang QasemiZadeh, Kata Gábor, Haïfa Zargayouna, Davide Buscaldi, Anne-Kathrin Schumann

Publikováno v: SemEval@NAACL-HLT
International Workshop on Semantic Evaluation (SemEval-2018)
International Workshop on Semantic Evaluation (SemEval-2018), Jun 2017, New Orleans, United States. pp.679-688

International audience; This paper describes the first task on semantic relation extraction and classification in scientific paper abstracts at SemEval 2018. The challenge focuses on domain-specific semantic relations and includes three different sub

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d609d16550e47f214ea1c241ffcfc3c
https://doi.org/10.18653/v1/s18-1111