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idMesh: graph-based disambiguation of linked data

Publications associées (32)

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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

Word Sense Consistency in Statistical and Neural Machine Translation

Xiao Pu

Different senses of source words must often be rendered by different words in the target language when performing machine translation (MT). Selecting the correct translation of polysemous words can be done based on the contexts of use. However, state-of-th ...

EPFL2018

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

EPFL2017

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

JRC-Names: Multilingual Entity Name variants and titles as Linked Data

Maud Ehrmann

Since 2004 the European Commission's Joint Research Centre (JRC) has been analysing the online version of printed media in over twenty languages and has automatically recognised and compiled large amounts of named entities (persons and organisations) and t ...

2016

A Method for Record Linkage with Sparse Historical Data

Maud Ehrmann, Yannick Rochat, Giovanni Colavizza

Massive digitization of archival material, coupled with automatic document processing techniques and data visualisation tools offers great opportunities for reconstructing and exploring the past. Unprecedented wealth of historical data (e.g. names of perso ...

2016

Kamusi Pre:D – Lexicon-based source-side predisambiguation for MT and other text processing applications

Martin Benjamin

Kamusi has been developing a system to analyze texts on the source side and present users with sense-specified dictionary options. Similarly to spellcheck, the user selects the intended meaning. We then use a multilingual lexical database to bridge to matc ...

ENeL2016

Contextualized ranking of entity types based on knowledge graphs

Karl Aberer, Philippe Cudré-Mauroux, Michele Catasta, Roman Prokofyev

A large fraction of online queries targets entities. For this reason, Search Engine Result Pages (SERPs) increasingly contain information about the searched entities such as pictures, short summaries, related entities, and factual information. A key facet ...

Elsevier Science Bv2016

Word Embeddings for Natural Language Processing

Rémi Philippe Lebret

Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...

EPFL2016

Building Word Embeddings for Solving Natural Language Processing

Rémi Philippe Lebret

École Polytechnique Fédérale de Lausanne2016