EntityCube is a research prototype and is a test bed for exploring object-level search technologies, which automatically summarizes the Web for entities (such as people, locations and organizations) with a substantial presence.
The Chinese-language version is called Renlifang.
The need for collecting and understanding Web information about a real-world entity (such as a person or a product) is currently fulfilled manually through search engines.
However, information about a single entity might appear in thousands of Web pages. Even if a search engine could find all the relevant Web pages about an entity, the user would need to sift through all these pages to get a complete view of the entity.
EntityCube generates summaries of Web entities from billions of public Web pages that contain information about people, locations, and organizations, and allows for exploration of their relationships. For example, users can use EntityCube to find an automatically generated biography page and social-network graph for a person, and use it to discover a relationship path between two people.
Please note that Microsoft is still working on improving the accuracy of the key machine learning problems including entity extraction, name disambiguation, entity ranking, and relationship extraction, as well as looking at a better way of incorporating user feedback.
