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Predicting Completeness in Knowledge Bases
Knowledge bases such as Wikidata, DBpedia, or YAGO contain millions of entities and facts. In some knowledge bases, the correctness of these facts has been evaluated. However, much less is knownExpand
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Enriching Knowledge Bases with Counting Quantifiers
Information extraction traditionally focuses on extracting relations between identifiable entities, such as \(\langle \)Monterey, locatedIn, California\(\rangle \). Yet, texts often also containExpand
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COOL-WD: A Completeness Tool for Wikidata
Wikidata as a collaborative Semantic Web data source has enjoyed increasing prominence, storing over 150 million facts about more than 26 million entities. Yet it is missing a way to assess itsExpand
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Commonsense Properties from Query Logs and Question Answering Forums
Commonsense knowledge about object properties, human behavior and general concepts is crucial for robust AI applications. However, automatic acquisition of this knowledge is challenging because ofExpand
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Enabling Completeness-aware Querying in SPARQL
Current RDF knowledge bases (KBs) are highly incomplete. This incompleteness is a serious problem both for data users and producers. Users do not have guarantees that queries that are run on a KBExpand
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Completeness of queries over incomplete databases
Data completeness is an important aspect of data quality as in many scenarios it is crucial to guarantee completeness of query answers. We develop techniques to conclude the completeness of queryExpand
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Completeness Statements about RDF Data Sources and Their Use for Query Answering
With thousands of RDF data sources available on the Web covering disparate and possibly overlapping knowledge domains, the problem of providing high-level descriptions (in the form of metadata) ofExpand
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But What Do We Actually Know?
Knowledge bases such as Wikidata, DBpedia, YAGO, or the Google Knowledge Vault collect a vast number of facts about the world. But while quite some facts are known about the world, little is knownExpand
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Identifying the Extent of Completeness of Query Answers over Partially Complete Databases
In many applications including loosely coupled cloud databases, collaborative editing and network monitoring, data from multiple sources is regularly used for query answering. For reasons such asExpand
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Completeness-Aware Rule Learning from Knowledge Graphs
Knowledge graphs (KGs) are huge collections of primarily encyclopedic facts. They are widely used in entity recognition, structured search, question answering, and other important tasks. Rule miningExpand
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