Information providers are faced with a critical challenge to process, retrieve and present information to their users in order to satisfy their complex information needs, because data has been increasing in an unprecedented manner, coming from diverse sources, and covering a variety of domains in heterogeneous formats. In this paper, we present Thomson Reuters' effort in developing a family of services for building and querying an enterprise knowledge graph in order to address this challenge. We first acquire data from various sources via different approaches. Furthermore, we mine useful information from the data by adopting a variety of techniques, including Named Entity Recognition and Relation Extraction; such mined information is further integrated with existing structured data (e.g., via Entity Linking techniques) in order to obtain relatively comprehensive descriptions of the entities. By modeling the data as an RDF graph model, we enable easy data management and the embedding of rich semantics in our data. Finally, in order to facilitate the querying of this mined and integrated data, i.e., the knowledge graph, we propose TR Discover, a natural language interface that allows users to ask questions of our knowledge graph in their own words; such natural language questions are then translated into executable queries for answer retrieval. We evaluate our services, i.e., named entity recognition, relation extraction, entity linking and natural language interface, on real-world datasets, and demonstrate and discuss their practicability and limitations.

This paper describes a highly scalable state of the art record aggregation system and the backbone infrastructure developed to support it. The system, called PeopleMap, allows legal professionals to effectively and efficiently explore a broad spectrum of public records databases by way of a single person-centric search. The backbone support system, called Concord, is a toolkit that allows developers to economically create record resolution solutions. The PeopleMap system is capable of linking billions of public records to a master data set consisting of hundreds of millions of person records. It was constructed using successive applications of Concord to link disparate public record data sets to a central person authority file. To our knowledge, the PeopleMap system is the largest of its kind. In contrast, the Concord support system is a novel record linkage tool that uses a new semi-supervised training technique called `surrogate learning' to enable the rapid development of record resolution solutions.