Papers with cognitive linguistics

4 papers
CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions (2022.findings-acl)

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Challenge: Existing models with similar physical and causal understanding capabilities are still underdeveloped.
Approach: They propose a video question answering dataset that requires causal reasoning about physical forces and object interactions.
Outcome: The proposed dataset requires causal reasoning about physical forces and object interactions.
Identification and Analysis of Personification in Hungarian: The PerSECorp project (2022.lrec-1)

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Challenge: despite recent findings on the conceptual and linguistic organization of personification, we have relatively little knowledge about its lexical patterns and grammatical templates.
Approach: They propose a corpus-driven approach to personification analysis in cognitive linguistics . they use a semi-automatically processed corpus to annotate personifying linguistic structures .
Outcome: The proposed method consists of annotating a semi-automatic corpus of car reviews in Hungarian . the corpus is structured and annotated manually, and gives an overview of possible data types .
Multilingual and Cross-Lingual Graded Lexical Entailment (P19-1)

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Challenge: a novel method for capturing graded (and binary) LE is developed for cross-lingual generalisation of lexical entailment . lexicale enlargement is a key principle behind hierarchical structure found in semantic networks .
Approach: They propose a method for cross-lingual generalisation of GR-LE relation using hyperlex and a bilingual dictionary.
Outcome: The proposed method outperforms current state-of-the-art on binary cross-lingual LE detection by a wide margin.
Language (Re)modelling: Towards Embodied Language Understanding (2020.acl-main)

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Challenge: Despite the rapid progress in NLU, current systems lack the rich mental representations that people use for language understanding.
Approach: They propose an approach to representation and learning based on the tenets of embodied cognitive linguistics (ECL) they propose a system architecture along with a roadmap towards realizing this vision.
Outcome: The proposed approach will improve the performance of existing systems and provide a roadmap towards realizing this vision.

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