IR like a SIR: Sense-enhanced Information Retrieval for Multiple Languages

Rexhina Blloshmi, Tommaso Pasini, Niccolò Campolungo, Somnath Banerjee, Roberto Navigli, Gabriella Pasi


Abstract
With the advent of contextualized embeddings, attention towards neural ranking approaches for Information Retrieval increased considerably. However, two aspects have remained largely neglected: i) queries usually consist of few keywords only, which increases ambiguity and makes their contextualization harder, and ii) performing neural ranking on non-English documents is still cumbersome due to shortage of labeled datasets. In this paper we present SIR (Sense-enhanced Information Retrieval) to mitigate both problems by leveraging word sense information. At the core of our approach lies a novel multilingual query expansion mechanism based on Word Sense Disambiguation that provides sense definitions as additional semantic information for the query. Importantly, we use senses as a bridge across languages, thus allowing our model to perform considerably better than its supervised and unsupervised alternatives across French, German, Italian and Spanish languages on several CLEF benchmarks, while being trained on English Robust04 data only. We release SIR at https://github.com/SapienzaNLP/sir.
Anthology ID:
2021.emnlp-main.79
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1030–1041
Language:
URL:
https://aclanthology.org/2021.emnlp-main.79
DOI:
10.18653/v1/2021.emnlp-main.79
Bibkey:
Cite (ACL):
Rexhina Blloshmi, Tommaso Pasini, Niccolò Campolungo, Somnath Banerjee, Roberto Navigli, and Gabriella Pasi. 2021. IR like a SIR: Sense-enhanced Information Retrieval for Multiple Languages. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1030–1041, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
IR like a SIR: Sense-enhanced Information Retrieval for Multiple Languages (Blloshmi et al., EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.79.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.79.mp4
Code
 sapienzanlp/sir