paper-with-me

홈 › Papers

Instances and concepts in distributional space

2017-04-01 · EACL 2017 4 · Gemma Boleda, Abhijeet Gupta, Sebastian Pad{\'o}

Instances ({`}Mozart{''}) are ontologically distinct from concepts or classes ({}composer{''}). Natural language encompasses both, but instances have received comparatively little attention in distributional semantics. Our results show that instances and concepts differ in their distributional properties. We also establish that instantiation detection ({}Mozart {--} composer{''}) is generally easier than hypernymy detection ({`}chemist {--} scientist{''}), and that results on the influence of input representation do not transfer from hyponymy to instantiation.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Differentiating Concepts and Instances for Knowledge Graph Embedding

2018-11-12 · EMNLP 2018 10 · Xin Lv, Lei Hou, Juanzi Li, Zhiyuan Liu

Concepts, which represent a group of different instances sharing common properties, are essential information in knowledge representation. Most conventional knowledge embedding methods encode both entities (concepts and …

Graph EmbeddingKnowledge Graph EmbeddingKnowledge GraphsLink Prediction+1

Zero-Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos

2015-12-02 · Mohamed Elhoseiny, Jingen Liu, Hui Cheng, Harpreet Sawhney 외

We propose a new zero-shot Event Detection method by Multi-modal Distributional Semantic embedding of videos. Our model embeds object and action concepts as well as other available modalities from videos into a distribut…

Event Detection

A Comprehensive Implementation of Conceptual Spaces

2017-07-14 · Lucas Bechberger, Kai-Uwe Kühnberger

The highly influential framework of conceptual spaces provides a geometric way of representing knowledge. Instances are represented by points and concepts are represented by regions in a (potentially) high-dimensional sp…

Employing distributional semantics to organize task-focused vocabulary learning

2020-11-22 · EACL (BEA) 2021 4 · Haemanth Santhi Ponnusamy, Detmar Meurers

How can a learner systematically prepare for reading a book they are interested in? In this paper,we explore how computational linguistic methods such as distributional semantics, morphological clustering, and exercise g…

Clustering

Words, Concepts, and the Geometry of Analogy

2016-08-04 · Stephen McGregor, Matthew Purver, Geraint Wiggins

This paper presents a geometric approach to the problem of modelling the relationship between words and concepts, focusing in particular on analogical phenomena in language and cognition. Grounded in recent theories rega…