A Survey on Semantic Processing Techniques
원문 초록
Semantic processing is a fundamental research domain in computational linguistics. In the era of powerful pre-trained language models and large language models, the advancement of research in this domain appears to be decelerating. However, the study of semantics is multi-dimensional in linguistics. The research depth and breadth of computational semantic processing can be largely improved with new technologies. In this survey, we analyzed five semantic processing tasks, e.g., word sense disambiguation, anaphora resolution, named entity recognition, concept extraction, and subjectivity detection. We study relevant theoretical research in these fields, advanced methods, and downstream applications. We connect the surveyed tasks with downstream applications because this may inspire future scholars to fuse these low-level semantic processing tasks with high-level natural language processing tasks. The review of theoretical research may also inspire new tasks and technologies in the semantic processing domain. Finally, we compare the different semantic processing techniques and summarize their technical trends, application trends, and future directions.
함께 살펴볼 논문
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Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
Label-Guided In-Context Learning for Named Entity Recognition
AmpleHate: Amplifying the Attention for Versatile Implicit Hate Detection
Named Entity Recognition in Historical Italian: The Case of Giacomo Leopardi's Zibaldone
A Case Study of Cross-Lingual Zero-Shot Generalization for Classical Languages in LLMs
Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations
토론
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