BERT Knows Punta Cana is not just beautiful, it's gorgeous: Ranking Scalar Adjectives with Contextualised Representations
Aina Garí Soler, Marianna Apidianaki
Abstract
Adjectives like pretty, beautiful and gorgeous describe positive properties of the nouns they modify but with different intensity. These differences are important for natural language understanding and reasoning. We propose a novel BERT-based approach to intensity detection for scalar adjectives. We model intensity by vectors directly derived from contextualised representations and show they can successfully rank scalar adjectives. We evaluate our models both intrinsically, on gold standard datasets, and on an Indirect Question Answering task. Our results demonstrate that BERT encodes rich knowledge about the semantics of scalar adjectives, and is able to provide better quality intensity rankings than static embeddings and previous models with access to dedicated resources.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext ac91e433-9462-4e2c-aa8c-085535eb7c31Cited by top-tier papers3
- Adjective Scale Probe: Can Language Models Encode Formal Semantics Information?Wei Liu, Ming Xiang, Nai DingAAAI 2023 · 7 citations
- Life after BERT: What do Other Muppets Understand about Language?Vladislav Lialin, Kevin Zhao, Namrata Shivagunde, Anna RumshiskyACL 2022 · 7 citations
- Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with PseudowordsTaelin Karidi, Yichu Zhou, Nathan Schneider, Omri Abend et al.EMNLP 2021
Builds on2
- A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector SpacesAnne Lauscher, Goran Glavas, Simone Paolo Ponzetto, Ivan VulicAAAI 2020 · 68 citations
- Null It Out: Guarding Protected Attributes by Iterative Nullspace ProjectionShauli Ravfogel, Yanai Elazar, Hila Gonen, Michael Twiton et al.ACL 2020 · 25 citations
Related papers
- Connecting degree and polarity: An artificial language learning studyLisa Bylinina, Alexey Tikhonov, Ekaterina GarmashEMNLP 2023
- Comparing a BERT Classifier and a GPT classifier for Detecting Connective Language Across Multiple Social MediaJosephine Lukito, Bin Chen, Gina M. Masullo, Natalie Jomini StroudEMNLP 2024
- Probing for the Usage of Grammatical NumberKarim Lasri, Tiago Pimentel, Alessandro Lenci, Thierry Poibeau et al.ACL 2022 · 72 citations
- Verb Metaphor Detection via Contextual Relation LearningWei Song, Shuhui Zhou, Ruiji Fu, Ting Liu et al.ACL 2021
- Analyzing How BERT Performs Entity MatchingMatteo Paganelli, Francesco Del Buono, Andrea Baraldi, Francesco GuerraVLDB 2022 · 35 citations
