Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical Forms

Unscoped Episodic Logical Forms (ULF) is a semantic representation for English sentences which captures semantic type structure, allows for linguistic inferences, and provides a basis for further resolution into Episodic Logic (EL). We present an application of pre-trained autoregressive language mo...

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Main Authors: Erin Gibson, Lane Lawley
Format: Article
Language:English
Published: LibraryPress@UF 2022-05-01
Series:Proceedings of the International Florida Artificial Intelligence Research Society Conference
Online Access:https://journals.flvc.org/FLAIRS/article/view/130703
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author Erin Gibson
Lane Lawley
author_facet Erin Gibson
Lane Lawley
author_sort Erin Gibson
collection DOAJ
description Unscoped Episodic Logical Forms (ULF) is a semantic representation for English sentences which captures semantic type structure, allows for linguistic inferences, and provides a basis for further resolution into Episodic Logic (EL). We present an application of pre-trained autoregressive language models to the task of rendering ULFs into English, and show that ULF's properties reduce the required training data volume for this approach when compared to AMR. We also show that the same system, when applied in reverse, performs well as an English-to-ULF parser.
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language English
publishDate 2022-05-01
publisher LibraryPress@UF
record_format Article
series Proceedings of the International Florida Artificial Intelligence Research Society Conference
spelling doaj-art-c08e82a6de334625a514e9d904871cbe2025-08-20T03:05:26ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622022-05-013510.32473/flairs.v35i.13070366902Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical FormsErin GibsonLane LawleyUnscoped Episodic Logical Forms (ULF) is a semantic representation for English sentences which captures semantic type structure, allows for linguistic inferences, and provides a basis for further resolution into Episodic Logic (EL). We present an application of pre-trained autoregressive language models to the task of rendering ULFs into English, and show that ULF's properties reduce the required training data volume for this approach when compared to AMR. We also show that the same system, when applied in reverse, performs well as an English-to-ULF parser.https://journals.flvc.org/FLAIRS/article/view/130703
spellingShingle Erin Gibson
Lane Lawley
Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical Forms
Proceedings of the International Florida Artificial Intelligence Research Society Conference
title Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical Forms
title_full Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical Forms
title_fullStr Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical Forms
title_full_unstemmed Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical Forms
title_short Language-Model-Based Parsing and English Generation for Unscoped Episodic Logical Forms
title_sort language model based parsing and english generation for unscoped episodic logical forms
url https://journals.flvc.org/FLAIRS/article/view/130703
work_keys_str_mv AT eringibson languagemodelbasedparsingandenglishgenerationforunscopedepisodiclogicalforms
AT lanelawley languagemodelbasedparsingandenglishgenerationforunscopedepisodiclogicalforms