Summary of Wiki-tabner:advancing Table Interpretation Through Named Entity Recognition, by Aneta Koleva et al.
Wiki-TabNER:Advancing Table Interpretation Through Named Entity Recognition
by Aneta Koleva, Martin Ringsquandl, Ahmed Hatem, Thomas Runkler, Volker Tresp
First submitted to arxiv on: 7 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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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 examines the use of web tables in tabular language models for tackling table interpretation (TI) tasks, specifically focusing on the entity linking task. A widely used benchmark dataset is analyzed, revealing that it is overly simplified, reducing its effectiveness and failing to accurately represent real-world tables. To overcome this limitation, a new, more challenging dataset is constructed and annotated. Additionally, a novel problem addressing named entity recognition within cells is introduced. The paper also proposes a prompting framework for evaluating large language models (LLMs) on this TI task. Experiments are conducted using random and similarity-based selection to choose examples presented to the models, while an ablation study provides insights into the impact of few-shot examples. Qualitative analysis helps understand challenges faced by models and limitations of the proposed dataset. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about how computers can better understand tables on the internet. Right now, there’s a problem with how we test these computer programs to make sure they’re good at understanding tables. The authors of this paper found that the tests are too easy and don’t show what really happens in the real world. To fix this, they created a new set of tests that are harder and more realistic. They also came up with a new challenge for computers: recognizing names within table cells. Finally, they developed a way to test how well these computer programs do on this new challenge. |
Keywords
» Artificial intelligence » Entity linking » Few shot » Named entity recognition » Prompting
