BERT Knows Punta Cana is not just beautiful, it's gorgeous: Ranking Scalar Adjectives with Contextualised Representations
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Abstract (arXiv)
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.
Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Oct 2020.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 5; 2024: 2; 2025: 3; 2026: 1.
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- 2023Unsupervised Contrast-Consistent Ranking with Language Modelscited by 13
- 2021Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with Pseudowordscited by 9
- 2023Expectations over Unspoken Alternatives Predict Pragmatic Inferencescited by 9
- 2023Representation Of Lexical Stylistic Features In Language Models' Embedding Spacecited by 8
- 2021Scalar Adjective Identification and Multilingual Rankingcited by 6
- 2022Life after BERT: What do Other Muppets Understand about Language?cited by 4
- 2024Adjusting Interpretable Dimensions in Embedding Space with Human Judgmentscited by 4
- 2022Using Paraphrases to Study Properties of Contextual Embeddingscited by 3
- 2024Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmaticscited by 3
- 2025Rethinking Word Similarity: Semantic Similarity through Classification Confusioncited by 2
- 2023Exploring Data Augmentation Methods on Social Media Corporacited by 0
- 2023Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language modelscited by 0
3 more
- 2025Extracting Conceptual Spaces from LLMs Using Prototype Embeddingscited by 0
- 2025Interpretable dimensions support an effect of agentivity and telicity on split intransitivitycited by 0
- 2026Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructionscited by 0
- 2026Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions29 May 2026
- 2025Interpretable dimensions support an effect of agentivity and telicity on split intransitivity20 Nov 2025
- 2025Extracting Conceptual Spaces from LLMs Using Prototype Embeddings23 Sep 2025
- 2025Rethinking Word Similarity: Semantic Similarity through Classification Confusion8 Feb 2025
- 2024Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics4 Apr 2024
- 2024Adjusting Interpretable Dimensions in Embedding Space with Human Judgments3 Apr 2024
- 2023Unsupervised Contrast-Consistent Ranking with Language Models13 Sep 2023
- 2023Representation Of Lexical Stylistic Features In Language Models' Embedding Space29 May 2023
- 2023Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language models25 May 2023
- 2023Expectations over Unspoken Alternatives Predict Pragmatic Inferences7 Apr 2023
- 2023Exploring Data Augmentation Methods on Social Media Corpora3 Mar 2023
- 2022Using Paraphrases to Study Properties of Contextual Embeddings12 Jul 2022
- 2023Unsupervised Contrast-Consistent Ranking with Language Modelscited by 13
- 2021Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with Pseudowordscited by 9
- 2023Expectations over Unspoken Alternatives Predict Pragmatic Inferencescited by 9
- 2023Representation Of Lexical Stylistic Features In Language Models' Embedding Spacecited by 8
- 2021Scalar Adjective Identification and Multilingual Rankingcited by 6
- 2022Life after BERT: What do Other Muppets Understand about Language?cited by 4
- 2024Adjusting Interpretable Dimensions in Embedding Space with Human Judgmentscited by 4
- 2022Using Paraphrases to Study Properties of Contextual Embeddingscited by 3
- 2024Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmaticscited by 3
- 2025Rethinking Word Similarity: Semantic Similarity through Classification Confusioncited by 2
- 2023Exploring Data Augmentation Methods on Social Media Corporacited by 0
- 2023Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language modelscited by 0
12 most cited of 15 All 15 (JSON)
- 2026Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions29 May 2026
- 2025Interpretable dimensions support an effect of agentivity and telicity on split intransitivity20 Nov 2025
- 2025Extracting Conceptual Spaces from LLMs Using Prototype Embeddings23 Sep 2025
- 2025Rethinking Word Similarity: Semantic Similarity through Classification Confusion8 Feb 2025
- 2024Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics4 Apr 2024
- 2024Adjusting Interpretable Dimensions in Embedding Space with Human Judgments3 Apr 2024
- 2023Unsupervised Contrast-Consistent Ranking with Language Models13 Sep 2023
- 2023Representation Of Lexical Stylistic Features In Language Models' Embedding Space29 May 2023
- 2023Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language models25 May 2023
- 2023Expectations over Unspoken Alternatives Predict Pragmatic Inferences7 Apr 2023
- 2023Exploring Data Augmentation Methods on Social Media Corpora3 Mar 2023
- 2022Using Paraphrases to Study Properties of Contextual Embeddings12 Jul 2022
12 newest of 15 All 15 (JSON)