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Design and Populate a Knowledge Graph storing the annotations of articles #1

@rtroncy

Description

@rtroncy

The demonstration at https://jde-predict.tools.eurecom.fr/ enables to submit any article from the JDE and to visualize a number of annotations on this article namely:

  • a prediction of the Business Events relevant for the given article (among 11 possible classes); 4 different algorithms are providing predictions together with a score.
  • a list of named entities extracted in the given article; 3 NER tools are used (spaCy, Flair, and a pre-trained CamemBERT model) and the final results include majority voting and other post-processing.
  • a prediction of the general themes (among 10 possible classes)

The goal is to materialize these annotations in a KG. The tasks are:

  • Design a lightweight model to represent/identify the news article and these annotations. The Business Events could be represented as skos:Concept in a dedicated ConceptScheme. Similarly, the Themes could also be represented as skos:Concept in another ConceptScheme. Named Entity annotations could re-use the NIF ontology.
  • Implement a converter for transforming the current JSON format in RDF to populate this KG
  • Propose in a README a number of useful SPARQL queries for this KG

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