DeFacto: Acquiring, Curating, and Using a Bilingual Domain Aware Commonsense Knowledge Base

DeFacto：获取、整理和使用双语领域感知常识知识库

• 批准号: RGPIN-2017-05068
• 负责人: Langlais, Philippe
• 金额: $ 1.68万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635068
• 关键词: DeFacto; Acquiring; Curating; Using; Bilingual

Automatically extracting knowledge from a large set of mostly unstructured documents (such as the Web) and organizing it into a knowledge base (KB) is a key challenge in artificial intelligence. Intuitively, such KBs should directly impact the quality of many NLP applications such as question answering, information retrieval or Text Analytics. Open information extraction, the task of extracting knowledge from texts without much supervision (especially not a prescription of the kind of information to mine), has brought new hope for such an endeavour.

从大量非结构化文档（如Web）中自动提取知识并将其组织到知识库（KB）中是人工智能的一个关键挑战。直观地说，这些知识库应该直接影响许多NLP应用程序的质量，例如问答，信息检索或文本分析。开放式信息提取，即在没有太多监督的情况下从文本中提取知识的任务（特别是没有对我的信息类型的规定），为这种努力带来了新的希望。