Abstract
We address the task of entity-relationship (E-R) retrieval, i.e, given a query characterizing types of two or more entities and relationships between them, retrieve the relevant tuples of related entities. Answering E-R queries requires gathering and joining evidence from multiple unstructured documents. In this work, we consider entity and relationships of any type, i.e, characterized by context terms instead of pre-defined types or relationships. We propose a novel IR-centric approach for E-R retrieval, that builds on the basic early fusion design pattern for object retrieval, to provide extensible entity-relationship representations, suitable for complex, multi-relationships queries. We performed experiments with Wikipedia articles as entity representations combined with relationships extracted from ClueWeb-09-B with FACC1 entity linking. We obtained promising results using 3 different query collections comprising 469 E-R queries.
Original language | English |
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Pages (from-to) | 49-54 |
Number of pages | 6 |
Journal | CEUR Workshop Proceedings |
Volume | 1883 |
Publication status | Published - 2017 |
Externally published | Yes |
Event | 1st Workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis, KG4IR 2017 - Shinjuku, Tokyo, Japan Duration: 11 Aug 2017 → … |