CAMRA: Copilot for AMR Annotation
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Abstract (arXiv)
In this paper, we introduce CAMRA (Copilot for AMR Annotatations), a cutting-edge web-based tool designed for constructing Abstract Meaning Representation (AMR) from natural language text. CAMRA offers a novel approach to deep lexical semantics annotation such as AMR, treating AMR annotation akin to coding in programming languages. Leveraging the familiarity of programming paradigms, CAMRA encompasses all essential features of existing AMR editors, including example lookup, while going a step further by integrating Propbank roleset lookup as an autocomplete feature within the tool. Notably, CAMRA incorporates AMR parser models as coding co-pilots, greatly enhancing the efficiency and accuracy of AMR annotators. To demonstrate the tool's capabilities, we provide a live demo accessible at: https://camra.colorado.edu
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References · 6
- 2021Evaluating Large Language Models Trained on Codecited by 8,320
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
- 2020CoRefi: A Crowd Sourcing Suite for Coreference Annotationcited by 12
- 2023How Good is the Model in Model-in-the-loop Event Coreference Resolution Annotation?cited by 4
- 2019AMR Normalization for Fairer Evaluationcited by 3
- 2016HUME: Human UCCA-Based Evaluation of Machine Translationcited by 2
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