MAPS-KB: A Million-scale Probabilistic Simile Knowledge Base
The ability to understand and generate similes is an imperative step to realize human-level AI. However, there is still a considerable gap between machine intelligence and human cognition in similes, since deep models based on statistical distribution tend to favour high-frequency similes. Hence, a large-scale symbolic knowledge base of similes is required, as it contributes to the modeling of diverse yet unpopular similes while facilitating additional evaluation and reasoning. To bridge the gap, we propose a novel framework for large-scale simile knowledge base construction, as well as two probabilistic metrics which enable an improved understanding of simile phenomena in natural language. Overall, we construct MAPS-KB, a million-scale probabilistic simile knowledge base, covering 4.3 million triplets over 0.4 million terms from 70 GB corpora. We conduct sufficient experiments to justify the effectiveness and necessity of the methods of our framework. We also apply MAPS-KB on three downstream tasks to achieve state-of-the-art performance, further demonstrating the value of MAPS-KB.
Code (2)
Tasks
Knowledge Base ConstructionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Writing Polishment with Simile: Task, Dataset and A Neural Approach
A simile is a figure of speech that directly makes a comparison, showing similarities between two different things, e.g. "Reading papers can be dull sometimes,like watching grass grow". Human writers often interpolate ap…
Can Pre-trained Language Models Interpret Similes as Smart as Human?
Simile interpretation is a crucial task in natural language processing. Nowadays, pre-trained language models (PLMs) have achieved state-of-the-art performance on many tasks. However, it remains under-explored whether PL…
Sentiment AnalysisSentiment ClassificationCan Pre-trained Language Models Interpret Similes as Smart as Human?
Simile interpretation is a crucial task in natural language processing. Nowadays, pre-trained language models (PLMs) have achieved state-of-the-art performance on many tasks. However, it remains under-explored whether PL…
Sentiment AnalysisSentiment ClassificationGenerating similes effortlessly like a Pro: A Style Transfer Approach for Simile Generation
Literary tropes, from poetry to stories, are at the crux of human imagination and communication. Figurative language such as a simile go beyond plain expressions to give readers new insights and inspirations. In this pap…
Common Sense ReasoningSentenceStyle TransferProbing Simile Knowledge from Pre-trained Language Models
Simile interpretation (SI) and simile generation (SG) are challenging tasks for NLP because models require adequate world knowledge to produce predictions. Previous works have employed many hand-crafted resources to brin…
DiversityLanguage ModellingPositionWorld Knowledge