Summary of X-amr Annotation Tool, by Shafiuddin Rehan Ahmed et al.
X-AMR Annotation Tool
by Shafiuddin Rehan Ahmed, Jon Z. Cai, Martha Palmer, James H. Martin
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed X-AMR annotation tool is a novel approach for annotating key corpus-level event semantics, leveraging machine assistance through the Prodigy Annotation Tool. The tool aims to enhance the user experience and ensure ease and efficiency in the annotation process. Empirical analyses demonstrate its effectiveness when integrated with GPT-4, highlighting its advantages over existing methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The X-AMR annotation tool helps identify key events in documents, making it easier for machines to understand what’s happening. By using a special tool called Prodigy, humans can work together with computers to annotate large collections of text. This makes it faster and more accurate than doing it by hand. The tool is especially useful when used with GPT-4, which helps computers understand the relationships between events. |
Keywords
* Artificial intelligence * Gpt * Semantics
