Summary of Relik: Retrieve and Link, Fast and Accurate Entity Linking and Relation Extraction on An Academic Budget, by Riccardo Orlando et al.
ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
by Riccardo Orlando, Pere-Lluis Huguet Cabot, Edoardo Barba, Roberto Navigli
First submitted to arxiv on: 31 Jul 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 ReLiK is a Retriever-Reader architecture proposed for Entity Linking (EL) and Relation Extraction (RE) in Natural Language Processing. It comprises two modules: the Retriever identifies candidate entities or relations, while the Reader discerns relevant retrieved entities or relations and aligns them with textual spans. The input representation incorporates candidate entities or relations alongside text, enabling single forward pass linking or extraction and leveraging pre-trained language models’ contextualization capabilities. This formulation achieves state-of-the-art performance in both in-domain and out-of-domain benchmarks using academic budget training and up to 40x inference speed compared to competitors. The architecture can be seamlessly applied for Information Extraction (cIE) by employing a shared Reader that simultaneously extracts entities and relations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ReLiK is a new way to do two important things in computer science: finding the meaning of words and phrases (Entity Linking), and identifying relationships between them (Relation Extraction). It’s like having a super-smart librarian who can find all the relevant information for you. This paper shows that ReLiK is really good at doing these things, even better than other systems, and it does it quickly too! The authors also show how this system can be used to do even more complex tasks, like finding all the important information in a piece of text. |
Keywords
» Artificial intelligence » Entity linking » Inference » Natural language processing
