Patents Phrase to Phrase Semantic Matching Dataset
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Abstract (arXiv)
There are many general purpose benchmark datasets for Semantic Textual Similarity but none of them are focused on technical concepts found in patents and scientific publications. This work aims to fill this gap by presenting a new human rated contextual phrase to phrase matching dataset. The entire dataset contains close to 50,000 rated phrase pairs, each with a CPC (Cooperative Patent Classification) class as a context. This paper describes the dataset and some baseline models.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 14 references that are in the map. First posted on arXiv 1 Aug 2022.
Builds on
6 of 14 references.
References · 6
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
- 2017SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluationcited by 1,001
- 2016Bag of Tricks for Efficient Text Classificationcited by 876
- 2017Advances in Pre-Training Distributed Word Representationscited by 207
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1.
3 papers.