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建模隐喻意义:对预测算法进行系统测试
Hamad Al-Azary1, J Nick Reid2, Paula Lauren3
1Lawrence Technological University, Southfield, MI, USA. halazary@ltu.edu.
Memory & cognition
|September 4, 2024
概括
隐喻处理的计算模型通常假定方向性,但这项研究发现Kintsch的预测算法类似地模拟标准和反向隐喻,挑战其独特的可行性.
科学领域:
- 认知心理学 认知心理学
- 计算语言学 计算语言学
- 心理语言学 心理语言学
背景情况:
- 隐喻通常是不可逆转的 (例如",律师是鱼",但不是"鱼是律师").
- 金茨的预测算法模拟了隐喻理解,假设方向语义处理.
- 预测算法的定向假设尚未被系统测试.
研究的目的:
- 系统地测试预测算法的性能与竞争对手的算法.
- 评估算法的区分正典和反向隐喻的能力.
- 挑战隐喻理解中的定向语义处理假设.
主要方法:
- 测试了预测算法和竞争对手的计算模型.
- 模拟的隐喻理解使用规范 ("律师是鱼") 和反向 ("鱼是律师") 形式.
- 对比模拟输出以评估定向处理和模型可行性.
主要成果:
- 预测算法的性能与更简单的竞争对手算法相美.
- 该算法为正规隐喻和反向隐喻产生了类似的模拟.
- 这些发现与预测算法的假定方向性相矛盾.
结论:
- 预测算法,如实施,可能不是一个独特的可行的模型,用于隐喻处理.
- 在隐喻理解中,对定向语义处理的假设需要进一步研究.
- 结果对开发隐喻的计算和心理语言模型有影响.
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