Automatic Extraction of Relationships among Motivations, Emotions and Actions from Natural Language Texts

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1. Verfasser: Yang, Fei
Format: Preprint
Veröffentlicht: 2024
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author Yang, Fei
author_facet Yang, Fei
contents We propose a new graph-based framework to reveal relationships among motivations, emotions and actions explicitly given natural language texts. A directed acyclic graph is designed to describe human's nature. Nurture beliefs are incorporated to connect outside events and the human's nature graph. No annotation resources are required due to the power of large language models. Amazon Fine Foods Reviews dataset is used as corpus and food-related motivations are focused. Totally 92,990 relationship graphs are generated, of which 63% make logical sense. We make further analysis to investigate error types for optimization direction in future research.
format Preprint
id arxiv_https___arxiv_org_abs_2408_00966
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Automatic Extraction of Relationships among Motivations, Emotions and Actions from Natural Language Texts
Yang, Fei
Computation and Language
We propose a new graph-based framework to reveal relationships among motivations, emotions and actions explicitly given natural language texts. A directed acyclic graph is designed to describe human's nature. Nurture beliefs are incorporated to connect outside events and the human's nature graph. No annotation resources are required due to the power of large language models. Amazon Fine Foods Reviews dataset is used as corpus and food-related motivations are focused. Totally 92,990 relationship graphs are generated, of which 63% make logical sense. We make further analysis to investigate error types for optimization direction in future research.
title Automatic Extraction of Relationships among Motivations, Emotions and Actions from Natural Language Texts
topic Computation and Language
url https://arxiv.org/abs/2408.00966