Semantic Role Labeling (SRL) is deeply dependent on complex linguistic resources and sophisticated neural models, which makes the task difficult to approach for non-experts. To address this issue we present a new platform named Intelligible Verbs and Roles (InVeRo). This platform provides access to a new verb resource, VerbAtlas, and a state-of-the-art pre-trained implementation of a neural, span-based architecture for SRL. Both the resource and the system provide human-readable verb sense and semantic role information, with an easy to use Web interface and RESTful APIs available at http://nlp.uniroma1.it/invero.
InVeRo: Making Semantic Role Labeling Accessible with Intelligible Verbs and Roles / Conia, Simone; Brignone, Fabrizio; Zanfardino, Davide; Navigli, Roberto. - (2020), pp. 77-84. (Intervento presentato al convegno Empirical Methods in Natural Language Processing tenutosi a Online) [10.18653/v1/2020.emnlp-demos.11].
InVeRo: Making Semantic Role Labeling Accessible with Intelligible Verbs and Roles
Conia, Simone
Primo
;Brignone, Fabrizio
Secondo
;Navigli, Roberto
Ultimo
2020
Abstract
Semantic Role Labeling (SRL) is deeply dependent on complex linguistic resources and sophisticated neural models, which makes the task difficult to approach for non-experts. To address this issue we present a new platform named Intelligible Verbs and Roles (InVeRo). This platform provides access to a new verb resource, VerbAtlas, and a state-of-the-art pre-trained implementation of a neural, span-based architecture for SRL. Both the resource and the system provide human-readable verb sense and semantic role information, with an easy to use Web interface and RESTful APIs available at http://nlp.uniroma1.it/invero.File | Dimensione | Formato | |
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