Work

UBC: Cubes for English Semantic Textual Similarity and Supervised Approaches for Interpretable STS

Year: 2015

Type: conference-paper

Abstract: In Semantic Textual Similarity, systems rate the degree of semantic equivalence on a graded scale from 0 to 5, with 5 being the most similar.For the English subtask, we present a system which relies on several resources for token-to-token and phrase-to-phrase similarity to build a data-structure which holds all the information, and then combine the information to get a similarity score.We also participated in the pilot on Interpretable STS, where we apply a pipeline which first aligns tokens, then chunks, and finally uses supervised systems to label and score each chunk alignment.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/s15-2032

Authors: Eneko Agirre, Aitor Gonzalez-Agirre, Inigo Lopez-Gazpio, Montse Maritxalar, German Rigau, Larraitz Uria

Institution: University of the Basque Country

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid