Espresso: Explaining Relationships between Entity Sets

Espresso is a system to compute semantically meaningful substructures (so-called relatedness cores) from a knowledge graph. The purpose of the system is to answer questions of the form «Which European politicians are related to politicians in the United States and how?» or «How can one summarize the relationship between China and countries from the Middle East over the last five years?» In this setting, a question is specified by means of two sets of query entities. These sets (e.g. "European politicians" or "United States politicians") can be determined by an initial graph query over a knowledge graph capturing relationships between real-world entities. As a next step, we analyze the (indirect) relationships that connect entities from both sets (e. g. membership in organizations, statements made on TV, etc.), generate an informative and concise result, and finally provide a user-friendly explanation of the answer. As output, we aim to return concise subgraphs corresponding to important event complexes, that connect entities from the two sets and explain their relationships. Espresso provides a user interface for the specification of entity sets, computes informative relatedness cores that summarize the relationship between the query entities, and finally displays a visually appealing visualization of the extracted subgraph to the user. Applications of the proposed system include scenarios that require to provide background information on the current state-of-affairs between real-world entities such as politicians, organizations, and the like, e. g. to a journalist preparing an article involving the entities of interest.

Publications

  • Espresso: Explaining Relationships between Entity Sets
    Stephan Seufert, Klaus Berberich, Srikanta J. Bedathur, Sarath Kumar Kondreddi, Patrick Ernst, and Gerhard Weikum
    Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016),
    Indianapolis, IN, United States, October 24-28, 2016. ACM.
  • Instant Espresso: Interactive Analysis of Relationships in Knowledge Graphs (Demo)
    Stephan Seufert, Patrick Ernst, Srikanta J. Bedathur, Sarath Kumar Kondreddi, Klaus Berberich, and Gerhard Weikum
    Proceedings of the 25th International World Wide Web Conference (WWW 2016),
    Montreal, QC, Canada, April 11-15, 2016. ACM.
  • Efficient Computation of Relationship-Centrality in Large Entity-Relationship Graphs (poster) 
    Stephan Seufert,  Srikanta J. Bedathur, Johannes Hoffart, Andrey Gubichev, and Klaus Berberisch
    Posters and Demonstrations Track of the 12th International Semantic Web Conference (ISWC 2013),
    Sydney, NSW, Australia, October 21-25, 2013.

People

Datasets

Name Description Fields Link Size
ClueWeb12 Cooccurrence Entity-cooccurences in ClueWeb entity1,entity2,count Download 728M
Entity Collection of all entities id, yagoid, freebaseid, wpid, name, readable yagoid, event (t/f) Download 117M
YAGO Types Collection of YAGO types id,name Download 4.6M
Entity-YAGO Type Association of entity with YAGO type entity,type Download 169M
Freebase Types Collection of Freebase types id,name Download 64K
Entity-Freebase Type Association of entity with Freebase type entity,type Download 29M
Links Links between entities source,target,MW-similarity,KORE-similarity Download 798M
Relations Collection of relations id,name,count Download 423
Link-Relations Association of links with relations source,target,relation Download 259M
Popularity Entity popularities based on pageviews entity,pop Download 34M
Views Pageviews for entities entity,day,count,Z-score,relative popularity Download 32G
Snippets Short textual entity descriptions from Wikipedia entity,snippet Download 462M
ClueWeb12 Counts Number of entity occurrences in ClueWeb entity,count Download 8.4M

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