NIST TAC SM-KBP 2019 System Description: JHU/UR Framework
Year: 2019
Type: article
Abstract: We designed and constructed a pipeline system for the Streaming Multimedia Knowledge Base Population (SM-KBP) 2019 evaluation. Our pipeline consists of a series of Information Extraction and Machine Translation components, supporting the population of knowledge graphs from a multilingual corpus (see Figure 1). Some of our key contributions include: a new dataset supporting event argument linking across multiple sentences; a novel algorithm for predicting such linkages, even when arguments are not co-referent with mentions in the same sentence as the event trigger; and a novel algorithm for supporting hierarchical typing of events, relations and entities.
Source: HAL
Institutions: Johns Hopkins University, University of Rochester
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3158436747