Summary of Guided Distant Supervision For Multilingual Relation Extraction Data: Adapting to a New Language, by Alistair Plum et al.
Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Language
by Alistair Plum, Tharindu Ranasinghe, Christoph Purschke
First submitted to arxiv on: 25 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
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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 addresses the challenge of extracting biographical relationships in digital humanities and related subjects, particularly in German, where datasets are limited to English. To overcome the limitations of expensive and time-consuming manual annotation, guided distant supervision is applied to create a large biographical relationship extraction dataset for German. The resulting dataset consists of over 80,000 instances across nine relationship types, making it the largest such dataset available. Additionally, a manually annotated dataset with 2,000 instances is created for evaluating machine learning models. State-of-the-art models are trained on the automatically generated dataset and released alongside the dataset. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us better understand people’s lives by finding connections between facts about them. This is important in digital humanities, which is a field that studies how humans express themselves through various forms of media. However, there’s a problem: we don’t have enough data to train computers to do this job well, especially not for languages like German. To fix this, the authors created a huge dataset with over 80,000 examples of biographical relationships. This will help researchers train machines to find connections between facts about people, even if those facts are in German. |
Keywords
* Artificial intelligence * Machine learning
