Summary of Classification Of Geological Borehole Descriptions Using a Domain Adapted Large Language Model, by Hossein Ghorbanfekr et al.
Classification of Geological Borehole Descriptions Using a Domain Adapted Large Language Model
by Hossein Ghorbanfekr, Pieter Jan Kerstens, Katrijn Dirix
First submitted to arxiv on: 24 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG); Geophysics (physics.geo-ph)
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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 This paper introduces GEOBERTje, a domain-adapted large language model trained on geological borehole descriptions in Dutch to extract relevant features into a structured format. The model is finetuned for categorizing borehole descriptions into lithology classes, outperforming rule-based approaches and GPT-4 of OpenAI. This study demonstrates how domain-adapted models enhance efficiency and accuracy in extracting information from complex, unstructured geological data, offering new opportunities for geological analysis and modeling. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary GEOBERTje is a special kind of computer program that helps scientists understand the composition of the Earth’s subsurface by organizing information from old reports. These reports are like puzzles with lots of details, but they’re hard to use because they’re not organized well. GEOBERTje can take these reports and turn them into something easy to understand, making it easier for scientists to learn about what’s below our feet. |
Keywords
* Artificial intelligence * Gpt * Large language model
