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Contextualized ranking of entity types based on knowledge graphs

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Capturing Types

Martin Odersky, Aleksander Slawomir Boruch-Gruszecki, Ondrej Lhoták

Type systems usually characterize the shape of values but not their free variables. However, many desirable safety properties could be guaranteed if one knew the free variables captured by values. We describe CC

New York2023

Who was afraid of Yuri Mikhailovich and why? (peculiarities of the reception of the Tartu version of structuralism after the 1960s)

Alexander Dmitriev

The paper discussed different types of reactions to the emergence of Yuri Lotman's structuralism in the Soviet Union after 1960 ...

2023

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Named entity linking (NEL) in news is a challenging endeavour due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods. However, such methods tend to come with caveats, such as no integration of ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2022

HIPE-2022 datasets used for the HIPE 2022 shared task on named entity recognition and classification (NERC) and entity linking (EL) in multilingual historical documents. HIPE-2022 datasets are based on six primary datasets assembled and prepared for the sh ...

2022

Virtual ADTs for Portable Metaprogramming

Martin Odersky, Nicolas Alexander Stucki

Scala 3 provides a metaprogramming interface that represents the abstract syntax tree definitions using algebraic data types. To allow the compiler to freely evolve without breaking the metaprogramming interface, we present virtual algebraic data types (or ...

ASSOC COMPUTING MACHINERY2021

Low-Rank Subspaces for Unsupervised Entity Linking

Robert West, Akhil Arora, Alberto Garcia Duran

Entity linking is an important problem with many applications. Most previous solutions were designed for settings where annotated training data is available, which is, however, not the case in numerous domains. We propose a light-weight and scalable entity ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation

Robert West, Eda Bayram, Alberto Garcia Duran

The existing literature on knowledge graph completion mostly focuses on the link prediction task. However, knowledge graphs have an additional incompleteness problem: their nodes possess numerical attributes, whose values are often missing. Our approach, d ...

2020

Named Entity Processing for Historical Texts

Maud Ehrmann, Matteo Romanello

Recognition and identification of real-world entities is at the core of virtually any text mining application. As a matter of fact, referential units such as names of persons, locations and organizations underlie the semantics of texts and guide their inte ...

2019

Classification methods from machine learning are receiving a lot of attention in the transportation modelling community. This is motivated by the access to large databases, and to various success stories reported in this research community. Discrete choice ...

2019

deepschema.org: An Ontology for Typing Entities in the Web of Data

Karl Aberer, Michele Catasta, Panagiotis Smeros, Amit Gupta

Discovering the appropriate type of an entity in the Web of Data is still considered an open challenge, given the complexity of the many tasks it entails. Among them, the most notable is the definition of a generic and cross-domain ontology. While the onto ...

2017