Linguistic ambiguity is and has always been one of the main challenges in Natural Language Processing (NLP) systems. Modern Transformer architectures like BERT, T5 or more recently InstructGPT have achieved some impressive improvements in many NLP fields, but there is still plenty of work to do. Motivated by the uproar caused by ChatGPT, in this paper we provide an introduction to linguistic ambiguity, its varieties and their relevance in modern NLP, and perform an extensive empiric analysis. ChatGPT strengths and weaknesses are revealed, as well as strategies to get the most of this model.
翻译：语言模糊是而且一直是自然语言处理(NLP)系统的主要挑战之一。 BERT、T5或最近更近一些的指令GPT等现代变革型结构在许多NLP领域取得了令人印象深刻的改进,但仍有许多工作要做。 本文对ChatGPT引起的高调进行了启发,介绍了语言模糊性、其品种及其在现代NLP中的相关性,并进行了广泛的语言分析。 热GPT的长处和短处暴露了出来,以及最充分利用这一模式的战略。
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