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Implementing the Storyline Ontology in BBC News


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Implementing the Storyline Ontology in BBC News

  1. 1. The Storyline Ontology Jeremy Tarling @jeremytarling Data Architect BBC News
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  3. 3. semantic annotation cwork: CreativeWork cwork: tag cwork: BlogPost cwork: Gallery core: Thing storyline: event storyline ontology core news ontology rdfs:subClassOf rdfs:subClassOf rdfs:Domain rdfs:Range cwork: Video cwork: NewsArticle rdfs:subClassOf news:Place news:Event news:Person /Organisatio news:Theme rdfs:subClassOf cwork: etc... cwork: mentions cwork: about rdfs:subPropertyOf
  4. 4. journalists „tagging‟ annotating (“tagging”) content tool embedded into CMS concept extraction/NLP for topic suggestion journalists accept/reject suggested topics
  5. 5. pilot – location tagging it worked… except when big stories broke we write several articles about the same storyline
  6. 6. articles… storytelling is fragmented manual linking decays massive amount of repetition
  7. 7. from articles to storylines develop a data model to describe a news storyline and its topics refine our content model to handle granular updates (A/V clip, short-form, social media update, long-form) ask journalists to annotate („tag‟) these updates with their storyline
  8. 8. collaborative model development
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  13. 13. an example storyline
  14. 14. linking storylines
  15. 15. linking events
  16. 16. tag storylines with topics…
  17. 17. topics topics are real-world entities, or things people organisations places themes
  18. 18. people a Person can have properties like „birth-place‟, „birth-date‟, and roles like „President of Syria‟ or „interpreter‟ Thamsanqa Jantjie Nick RobinsonLara Clarke Bashar al-Assad
  19. 19. organisations an Organisation can have properties like „address‟, „website‟, and can be notably associated with a person, place or theme
  20. 20. places Places can have a latitudes/longitudes and parent features (an administrative district or country for example)
  21. 21. themes Themes are the intangible things that we might want to classify our content by: „smoking‟, „unemployment‟, „health‟ health unemployment smoking
  22. 22. tagging with a topic <:thing> :type <:video> <:thing> :about <:David Cameron> but is this video clip really about the topic of David Cameron?
  23. 23. about-ness?
  24. 24. tagging with a storyline <:thing> :type <:video> <:thing> :about <:storyline> <:storyline> :slug “Cameron EU statement” <:storyline> :topic <:David Cameron> <:storyline> :topic <:European Union> <:storyline> :attribution <:Nick Robinson>
  25. 25. topics connect storylines
  26. 26. curation vs automation two ways to present tagged content: automatic aggregations where all content tagged with that storyline, event or topic is included in a chronological stream manual curations where a journalist picks and orders content in order to tell a particular story
  27. 27. automatic aggregation
  28. 28. anything with that storyline or topic tag automatically surfaces it in that stream this could be the default/out-of-hours state for a storyline or topic page less time-consuming, but no control over tone and sequence automatic aggregation
  29. 29. manual curation
  30. 30. more time consuming, but greater control candidate content is manually selected for inclusion in a storyline or topic page attribution – manually curated storylines can be attributed to a person or group (internally or publicly) manual curation
  31. 31. demo? production tagging with topics and storylines live pilot of storyline tagging in the Midlands