Browsing by Subject "knowledge base"
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Item Entity Disambiguation for Knowledge Base Population(2010-08-23) Dredze, Mark; McNamee, Paul; Rao, Delip; Gerber, Adam; Finin, TimThe integration of facts derived from information extraction systems into existing knowledge bases requires a system to disambiguate entity mentions in the text. This is challenging due to issues such as non-uniform variations in entity names, mention ambiguity, and entities absent from a knowledge base. We present a state of the art system for entity disambiguation that not only addresses these challenges but also scales to knowledge bases with several million entries using very little resources. Further, our approach achieves performance of up to 95% on entities mentioned from newswire and 80% on a public test set that was designed to include challenging queries.Item Evaluating the Quality of a Knowledge Base Populated from Text(ACM, 2012-06-07) Mayfield, James; Finin, TimThe steady progress of information extraction systems has been helped by sound methodologies for evaluating their performance in controlled experiments. Annual events like MUC, ACE and TAC have developed evaluation approaches enabling researchers to score and rank their systems relative to reference results. Yet these evaluations have only assessed component technologies needed by a knowledge base population system; none has required the construction of a knowledge base that is then evaluated directly. We describe an approach to the direct evaluation of a knowledge base and an instantiation that will be used in a 2012 TAC Knowledge Base Population track.Item HLTCOE Approaches to Knowledge Base Population at TAC 2009(National Institute of Standards and Technology, 2009-11-01) McNamee, Paul; Dredze, Mark; Gerber, Adam; Garera, Nikesh; Finin, Tim; Mayfield, James; Piatko, Christine; Rao, Delip; Yarowsky, David; Dreyer, MarkusThe HLTCOE participated in the entity linking and slot filling tasks at TAC 2009. A machine learning-based approach to entity linking, operating over a wide range of feature types, yielded good performance on the entity linking task. Slot-filling based on sentence selection, application of weak patterns and exploitation of redundancy was ineffective in the slot filling task.Item Interactive Knowledge Base Population(2015-05-15) Wolfe, Travis; Dredze, Mark; Mayfield, James; McNamee, PaulMost work on building knowledge bases has focused on collecting entities and facts from as large a collection of documents as possible. We argue for and describe a new paradigm where the focus is on a high-recall extraction over a small collection of documents under the supervision of a human expert, that we call Interactive Knowledge Base Population (IKBP).Item KELVIN: a tool for automated knowledge base construction(2013-06-03) McNamee, Paul; Mayfield, James; Finin, Tim; Oates, Tim; Lawrie, Dawn; Xu, Tan; Oard, DougWe present KELVIN, an automated system for processing a large text corpus and distilling a knowledge base about persons, organizations, and locations. We have tested the KELVIN system on several corpora, including: (a) the TAC KBP 2012 Cold Start corpus which consists of public Web pages from the University of Pennsylvania, and (b) a subset of 26k news articles taken from English Gigaword 5th edition. Our NAACL HLT 2013 demonstration permits a user to interact with a set of searchable HTML pages, which are automatically generated from the knowledge base. Each page contains information analogous to the semi-structured details about an entity that are present in Wikipedia Infoboxes, along with hyperlink citations to supporting text.Item OWL as a Target for Information Extraction Systems(2008-04-01) Fink, Clay; Finin, Tim; Mayfield, James; Piatko, ChristineCurrent information extraction systems can do a good job of discovering entities, relations and events in natural language text. The traditional output of such systems is XML, with the ACE Pilot Format (APF) schema as a common target. We are developing a system that will take the output of an information extraction system as APF documents and directly populate a knowledge base with the information extracted. We report on an initial OWL ontology that covers the APF schema, a simple program to convert a set of APF documents to RDF data and a demonstration system build with Exhibit to view the results.Item Swoogle: Searching for knowledge on the Semantic Web(AAAI, 2005-07-19) Finin, Tim; Ding, Li; Pan, Rong; Joshi, Anupam; Kolari, Pranam; Java, Akshay; Peng, YunSwoogle is an implemented system that discovers, analyzes and indexes knowledge encoded in semantic web documents on the Web. Swoogle reasons about these documents and their constituent parts (e.g., terms and triples) and records meaningful metadata about them. Swoogle provides webscale semantic web data access service, which helps human users and software systems to find relevant documents, terms and triples, via its search and navigation services. Swoogle also provides a customizable algorithm inspired by Google's PageRank algorithm but adapted to the semantics and use patterns found in semantic web documents.Item Text and Ontology Driven Clinical Decision Support System(American Medical Informatics Association (AMIA), 2013-10-31) Dhariwal, Deepal; Joshi, Anupam; Grasso, Michael A.In this paper, we discuss our ongoing research in the domain of text and ontology driven clinical decision support system. The proposed framework uses text analytics to extract clinical entities from electronic health records and semantic web analytics to generate a domain specific knowledge base (KB) of patients’ clinical facts. Clinical Rules expressed in the Semantic Web Language OWL are used to reason over the KB to infer additional facts about the patient. The KB is then queried to provide clinically relevant information to the physicians.