rebel-large
Maintainer: Babelscape
189
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
rebel-large is a relation extraction model developed by Babelscape. It takes a novel approach to relation extraction, framing it as a sequence-to-sequence task rather than a traditional classification task. This allows the model to generate natural language descriptions of the relations between entities, rather than just predicting a relation type. The model achieves state-of-the-art performance on several relation extraction benchmarks, including NYT, CoNLL04, and RE-TACRED.
Similar models include multilingual-e5-large, a multi-language text embedding model, bge-large-en-v1.5, BAAI's text embedding model, and GPT-2B-001, a large transformer-based language model.
Model inputs and outputs
Inputs
- Text: The model takes in a piece of text, typically a sentence or short paragraph, as input.
- Entity mentions: The model also requires that the entities mentioned in the text be identified and provided as input.
Outputs
- Relation description: The model outputs a natural language description of the relation between the provided entities.
Capabilities
rebel-large excels at extracting complex relations between entities within text. Unlike traditional relation extraction models that classify relations into a fixed set of types, rebel-large generates free-form descriptions of the relationships. This allows the model to capture nuanced and context-dependent relationships that may not fit neatly into predefined categories.
What can I use it for?
rebel-large can be used in a variety of applications that involve understanding the relationships between entities, such as knowledge graph construction, question answering, and text summarization. For example, a company could use rebel-large to automatically extract insights from financial reports or scientific literature, helping to surface important connections and trends.
Things to try
One interesting aspect of rebel-large is its ability to handle multi-hop relations, where the relationship between two entities is mediated by one or more intermediate entities. This could be explored further by experimenting with more complex input texts and seeing how well the model can uncover these intricate connections.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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