语言模型能否捕捉隐含的话语含义？一项基于韩语形态学穷尽含义的研究
Do language models capture implied discourse meanings? An investigation with exhaustivity implicatures of Korean morphology
AI总结：
本文通过韩语差异宾语标记考察大型语言模型能否捕捉隐含话语含义，发现语法标记的话语含义比话语标记更难被模型编码。
摘要：
自然语言中的标记性常常与话语中的非字面含义相关联。韩语中的差异宾语标记（Differential Object Marking, DOM）是这一现象的一个实例，其中后置标记的选择既基于名词短语的语义特征，也基于与语义特征正交的话语特征。此前的研究表明，分布式语言模型能够恢复词语的某些语义特征——这些模型是否也能捕捉隐含的话语层面含义？我们评估了一组大型语言模型是否能够将话语含义与韩语中不同的宾语标记联系起来。结果表明，语法标记的话语含义可能比话语标记的话语含义更难编码。
英文摘要：
Markedness in natural language is often associated with non-literal meanings in discourse. Differential Object Marking (DOM) in Korean is one instance of this phenomenon, where post-positional markers are selected based on both the semantic features of the noun phrases and the discourse features that are orthogonal to the semantic features. Previous work has shown that distributional models of language recover certain semantic features of words -- do these models capture implied discourse-level meanings as well? We evaluate whether a set of large language models are capable of associating discourse meanings with different object markings in Korean. Results suggest that discourse meanings of a grammatical marker can be more challenging to encode than that of a discourse marker.
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