# CuRIAM: Corpus re Interpretation and Metalanguage in U.S. Supreme Court Opinions

arXiv: https://arxiv.org/abs/2305.14719 · HTML: https://mlsanity.com/paper/2305.14719/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 66 references that are in the map.
- First posted on arXiv 24 May 2023.

## Builds on (most cited first, 6 of 6)

- [Learning to Understand Phrases by Embedding the Dictionary](https://mlsanity.com/paper/1504.00548/) (2015)
- [MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting](https://mlsanity.com/paper/2107.00414/) (2021)
- [SemEval-2020 Task 6: Definition extraction from free text with the DEFT corpus](https://mlsanity.com/paper/2008.13694/) (2020)
- [BERT for Monolingual and Cross-Lingual Reverse Dictionary](https://mlsanity.com/paper/2009.14790/) (2020)
- [DirectQuote: A Dataset for Direct Quotation Extraction and Attribution in News Articles](https://mlsanity.com/paper/2110.07827/) (2021)
- [ELQA: A Corpus of Metalinguistic Questions and Answers about English](https://mlsanity.com/paper/2205.00395/) (2022)

## Built on by (most cited first, 2 of 2)

- [I am a Strange Dataset: Metalinguistic Tests for Language Models](https://mlsanity.com/paper/2401.05300/) (2024)
- [Speaking of Language: Reflections on Metalanguage Research in NLP](https://mlsanity.com/paper/2604.02645/) (2026)

## Abstract (arXiv)

Most judicial decisions involve the interpretation of legal texts; as such, judicial opinion requires the use of language as a medium to comment on or draw attention to other language. Language used this way is called metalanguage. We develop an annotation schema for categorizing types of legal metalanguage and apply our schema to a set of U.S. Supreme Court opinions, yielding a corpus totaling 59k tokens. We remark on several patterns observed in the kinds of metalanguage used by the justices.