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        <title>Estimating Commonsense Knowledge from a Linguistic Analysis on Information Distribution</title>
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    <abstract>Commonsense Knowledge (CSK) is defined as a complex and multifaceted structure, encompassing a wide range of knowledge and reasoning generally acquired through everyday experiences. As CSK is often implicit in communication, it poses a challenge for AI systems to simulate human-like interaction. This work aims to deepen the CSK information structure from a linguistic perspective, starting from its organisation in conversations. To achieve this goal, we developed a three-level analysis model to extract more insights about this knowledge, focusing our attention on the second level. In particular, we aimed to extract the distribution of explicit actions and their execution order in the communicative flow. We built an annotation scheme based on FrameNet and applied it to a dialogical corpus on the culinary domain. Preliminary results indicate that certain frames occur earlier in the dialogues, while others occur towards the process’s end. These findings contribute to the systematic nature of actions by establishing clear patterns and relationships between frames.</abstract>
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%0 Conference Proceedings
%T Estimating Commonsense Knowledge from a Linguistic Analysis on Information Distribution
%A Mennella, Sabrina
%A Di Maro, Maria
%A Di Bratto, Martina
%S Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)
%D 2024
%8 September
%I Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences
%C Sofia, Bulgaria
%F mennella-etal-2024-estimating
%X Commonsense Knowledge (CSK) is defined as a complex and multifaceted structure, encompassing a wide range of knowledge and reasoning generally acquired through everyday experiences. As CSK is often implicit in communication, it poses a challenge for AI systems to simulate human-like interaction. This work aims to deepen the CSK information structure from a linguistic perspective, starting from its organisation in conversations. To achieve this goal, we developed a three-level analysis model to extract more insights about this knowledge, focusing our attention on the second level. In particular, we aimed to extract the distribution of explicit actions and their execution order in the communicative flow. We built an annotation scheme based on FrameNet and applied it to a dialogical corpus on the culinary domain. Preliminary results indicate that certain frames occur earlier in the dialogues, while others occur towards the process’s end. These findings contribute to the systematic nature of actions by establishing clear patterns and relationships between frames.
%U https://aclanthology.org/2024.clib-1.28
%P 257-263

Markdown (Informal)

[Estimating Commonsense Knowledge from a Linguistic Analysis on Information Distribution](https://aclanthology.org/2024.clib-1.28) (Mennella et al., CLIB 2024)

• Estimating Commonsense Knowledge from a Linguistic Analysis on Information Distribution (Mennella et al., CLIB 2024)

ACL

• Sabrina Mennella, Maria Di Maro, and Martina Di Bratto. 2024. Estimating Commonsense Knowledge from a Linguistic Analysis on Information Distribution. In Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024), pages 257–263, Sofia, Bulgaria. Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences.