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            <namePart type="given">Ali</namePart>
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        <name type="personal">
            <namePart type="given">Hristo</namePart>
            <namePart type="family">Tanev</namePart>
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        <name type="personal">
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    <abstract>As practitioners in the field of Natural Language Processing (NLP), we have had the unique vantage point of witnessing the evolutionary strides leading to the emergence of Large Language Models (LLMs) over the past decades. This perspective allows us to contextualise the current enthusiasm surrounding LLMs, especially following the introduction of “General Purpose” Language Models and the widespread adoption of conversational chatbots built on their frameworks. At the same time, we have observed the remarkable capabilities of zeroshot systems powered by LLMs in extracting structured information from text, outperforming previous iterations of language models. In this paper, we contend that that the hype around “conversational AI” is both a revolution and an epiphenomenon for NLP, particularly in the domain of information extraction from text. By adopting a measured approach to the recent technological advancements in Artificial Intelligence that are reshaping NLP, and by utilising Automated Socio-Political Event Extraction from text as a case study, this commentary seeks to offer insights into the ongoing trends and future directions in the field.</abstract>
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%0 Conference Proceedings
%T Natural Language Processing vs Large Language Models: this is the end of the world as we know it, and I feel fine
%A De Longueville, Bertrand
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Thapa, Surendrabikram
%S Proceedings of the 8th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Texts
%D 2025
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F de-longueville-2025-natural
%X As practitioners in the field of Natural Language Processing (NLP), we have had the unique vantage point of witnessing the evolutionary strides leading to the emergence of Large Language Models (LLMs) over the past decades. This perspective allows us to contextualise the current enthusiasm surrounding LLMs, especially following the introduction of “General Purpose” Language Models and the widespread adoption of conversational chatbots built on their frameworks. At the same time, we have observed the remarkable capabilities of zeroshot systems powered by LLMs in extracting structured information from text, outperforming previous iterations of language models. In this paper, we contend that that the hype around “conversational AI” is both a revolution and an epiphenomenon for NLP, particularly in the domain of information extraction from text. By adopting a measured approach to the recent technological advancements in Artificial Intelligence that are reshaping NLP, and by utilising Automated Socio-Political Event Extraction from text as a case study, this commentary seeks to offer insights into the ongoing trends and future directions in the field.
%U https://aclanthology.org/2025.case-1.4/
%P 32-37

Markdown (Informal)

[Natural Language Processing vs Large Language Models: this is the end of the world as we know it, and I feel fine](https://aclanthology.org/2025.case-1.4/) (De Longueville, CASE 2025)

• Natural Language Processing vs Large Language Models: this is the end of the world as we know it, and I feel fine (De Longueville, CASE 2025)

ACL

• Bertrand De Longueville. 2025. Natural Language Processing vs Large Language Models: this is the end of the world as we know it, and I feel fine. In Proceedings of the 8th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Texts, pages 32–37, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.