Knowledge Base Population

In this paper we give an overview of the Knowledge Base Population (KBP) track at the 2010 Text Analysis Conference. The main goal of KBP is to promote research in …...

Information extraction systems automati- cally extract structured information from machine-readable documents, such as newswire, web, and multimedia. Despite significant improvement, the performance is far from perfect. Hence, it is useful …...

AbstractNatural Language Processing (NLP) continues to grow in popularity in a range of research and commercial applications. However, installing, maintaining, and running NLP tools can be time consuming, and many …...

AbstractThis paper presents a German corpus for Named Entity Linking (NEL) and Knowledge Base Population (KBP) tasks. We describe the annotation guideline, the annotation process, NIL clustering techniques and conversion …...

We propose an algorithm that combines su- pervised and unsupervised methods to ensem- ble multiple systems for two popular Knowl- edge Base Population (KBP) tasks, Cold Start Slot Filling (CSSF) …...

AbstractKnowledge base population (KBP) systems take in a large document corpus and extract entities and their relations. Thus far, KBP evaluation has relied on judgements on the pooled predictions of …...

Knowledge Base Population (KBP) is an evaluation series within the Text Analysis Conference (TAC) evaluation campaign conducted by the National Institute of Standards and Technology (NIST). Over the past nine …...

AbstractThe study of linguistic typology is rooted in the implications we find between linguistic features, such as the fact that languages with object-verb word ordering tend to have postpositions. Uncovering …...

AbstractUnderstanding the structures of political debates (which actors make what claims) is essential for understanding democratic political decision making. The vision of computational construction of such discourse networks from newspaper …...