What do Deck Chairs and Sun Hats Have in Common? Uncovering Shared Properties in Large Concept Vocabularies
Concepts play a central role in many applications. This includes settings where concepts have to be modelled in the absence of sentence context. Previous work has therefore focused on distilling decontextualised concept embeddings from language models. But concepts can be modelled from different perspectives, whereas concept embeddings typically mostly capture taxonomic structure. To address this issue, we propose a strategy for identifying what different concepts, from a potentially large concept vocabulary, have in common with others. We then represent concepts in terms of the properties they share with the other concepts. To demonstrate the practical usefulness of this way of modelling concepts, we consider the task of ultra-fine entity typing, which is a challenging multi-label classification problem. We show that by augmenting the label set with shared properties, we can improve the performance of the state-of-the-art models for this task.
Code (0)
등록된 구현이 없습니다.
Tasks
Entity TypingMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONSentenceMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Characterizing the public perception of WhatsApp through the lens of media
WhatsApp is, as of 2018, a significant component of the global information and communication infrastructure, especially in developing countries. However, probably due to its strong end-to-end encryption, WhatsApp became …
ArticlesMisinformationHolodeck: Language Guided Generation of 3D Embodied AI Environments
3D simulated environments play a critical role in Embodied AI, but their creation requires expertise and extensive manual effort, restricting their diversity and scope. To mitigate this limitation, we present Holodeck, a…
Common Sense ReasoningLanguage ModellingLarge Language ModelNavigateTiplines to Combat Misinformation on Encrypted Platforms: A Case Study of the 2019 Indian Election on WhatsApp
There is currently no easy way to fact-check content on WhatsApp and other end-to-end encrypted platforms at scale. In this paper, we analyze the usefulness of a crowd-sourced "tipline" through which users can submit con…
MisinformationA Hierarchical Network-Oriented Analysis of User Participation in Misinformation Spread on WhatsApp
WhatsApp emerged as a major communication platform in many countries in the recent years. Despite offering only one-to-one and small group conversations, WhatsApp has been shown to enable the formation of a rich underlyi…
Misinformation"Short is the Road that Leads from Fear to Hate": Fear Speech in Indian WhatsApp Groups
WhatsApp is the most popular messaging app in the world. Due to its popularity, WhatsApp has become a powerful and cheap tool for political campaigning being widely used during the 2019 Indian general election, where it …