We approach the classification problem as an entailment problem and apply zero-shot ranking to socio-political texts. Documents that are ranked at the top can be considered positively classified documents and this reduces the close reading time for the information extraction process. We use Transformer Language Models to get the entailment probabilities and investigate different types of queries. We find that DeBERTa achieves higher mean average precision scores than RoBERTa and when declarative form of the class label is used as a query, it outperforms dictionary definition of the class label. We show that one can reduce the close reading time by taking some percentage of the ranked documents that the percentage depends on how much recall they want to achieve. However, our findings also show that percentage of the documents that should be read increases as the topic gets broader.

Zero-Shot Ranking Socio-Political Texts with Transformer Language Models to Reduce Close Reading Time

**Chair:** Ali Hürriyetoğlu **Organizers:** Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella, Tadashi Nomoto, Benjamin Radford, Milena Slavcheva, and Erdem Yörük 
**Invited speakers**: [J. Craig Jenkins](https://underline.io/speakers/212902-j.-craig-jenkins), [Scott Althaus](https://underline.io/speakers/212905-scott-althaus) and [Thien Huu Nguyen](https://underline.io/speakers/40729-thien-nguyen)
 Please visit our [**website**](https://emw.ku.edu.tr/case-2022/) for more information and detailed schedule. 
**Rocket channel for this workshop:** https://emnlp2022.rocket.chat/channel/workshop-1-case

 [**Live Session Recording - Day 1**](https://us06web.zoom.us/rec/play/7lXvGAHeFunqc7drItCsNDX8r5dOT-k28zCHHEELV9EytnckOe0wj0GBGitxhcuV4aKlkyTn7UxnsRq4.WDecGUCgdz2bEdW-?autoplay=true&startTime=1670386043000)
 
[**Live Session Recording - Day 2**](https://us06web.zoom.us/rec/play/DuXvqjg035NP1dnOgcQRop3wvW3c4bn_xrxLPineJpgI2Ra_3AKPM7GT1jI-hQlKTvKx4VJAwKjwxrYz.UJa5WCrjg5M2GMLX?autoplay=true&startTime=1670471578000)

W1 (CASE) The 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text 

workshop paper

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[![](https://assets.underline.io/uploads/markdown_image/1/image/9eec7d4a287ee18c278b08229290aa83.png)](https://drive.google.com/file/d/1OlPv6QBeo62VVTughj2jkiLeyHd1WnUt/view)
 
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EMNLP 2022 will take place in Abu Dhabi from December 7th to December 11th, 2022. And it will be held in hybrid mode, both online and offline.

Kiymet Akdemir

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Zero-Shot Ranking Socio-Political Texts with Transformer Language Models to Reduce Close Reading Time

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