Preface to the Special Issue Bridging Theoretical Linguistics and Automated Language Processing: Emerging Synergies and Advances
In recent years, Natural Language Processing (NLP) has gone through a radical breakthrough due to the success of Large Language Models (LLMs). These models have demonstrated that an unsupervised inductive approach, based on processing large amounts of raw data, can achieve extraordinary accuracy ra...
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| Veröffentlicht in: | URI:https://journals.openedition.org/ijcol, |
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| Hauptverfasser: | , , , |
| Format: | Article ou chapitre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
IJCoL
2026
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| Online Zugang: | Accès Université d'Orléans et IFPM |
| Zusammenfassung: | In recent years, Natural Language Processing (NLP) has gone through a radical breakthrough due to the success of Large Language Models (LLMs). These models have demonstrated that an unsupervised inductive approach, based on processing large amounts of raw data, can achieve extraordinary accuracy rates in many NLP-related tasks. This progress seems to have reduced the role of theoretical linguistics in computational approaches to linguistic analysis. For instance, metalinguistic annotation, a... |
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