A new approach for extracting the conceptual schema of texts based on the linguistic Thematic Progression theory
The purpose of this article is to present a new approach for the discovery and labelling of the implicit conceptual schema of texts through the application of the Thematic Progression theory. The underlying conceptual schema is the core component for the generation of summaries that are genuinely consistent with the semantics of the text.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Conceptual Networks for Cross-Linguistic Idiomatic Expressions:A Feature-Based Graph Approach
We present an interpretable network-based framework for representing idiomatic and figurative meaning across eight typologically diverse languages, totaling 160 conventional expressions, the large majority of which are i…
Cross-Lingual TransferCommunity DetectionExtracting semantic relations via the combination of inferences, schemas and cooccurrences
Extracting semantic relations from texts is a good way to build and supply a knowledge base, an indispensable resource for text analysis. We propose and evaluate the combination of three ways of producing lexical-semanti…
COPEN: Probing Conceptual Knowledge in Pre-trained Language Models
Conceptual knowledge is fundamental to human cognition and knowledge bases. However, existing knowledge probing works only focus on evaluating factual knowledge of pre-trained language models (PLMs) and ignore conceptual…
Knowledge ProbingDisentangling the schema turn: Restoring the information base to conceptual modelling
If one looks at contemporary mainstream development practices for conceptual modelling in computer science, these so clearly focus on a conceptual schema completely separated from its information base that the conceptual…
AI Blob! LLM-Driven Recontextualization of Italian Television Archives
This paper introduces AI Blob!, an experimental system designed to explore the potential of semantic cataloging and Large Language Models (LLMs) for the retrieval and recontextualization of archival television footage. D…
Speech Recognition