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The Storyline Ontology Jeremy Data Architect BBC News.

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Presentation on theme: "The Storyline Ontology Jeremy Data Architect BBC News."— Presentation transcript:

1 The Storyline Ontology Jeremy Data Architect BBC News

2

3 semantic annotation

4 journalists ‘tagging’ annotating (“tagging”) content tool embedded into CMS concept extraction/NLP for topic suggestion journalists accept/reject suggested topics

5 pilot – location tagging it worked… except when big stories broke we write several articles about the same storyline

6 articles… storytelling is fragmented manual linking decays massive amount of repetition

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 collaborative model development

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13 an example storyline

14 linking storylines

15 linking events

16 tag storylines with topics…

17 topics topics are real-world entities, or things people organisations places themes

18 people a Person can have properties like ‘birth-place’, ‘birth-date’, and roles like ‘President of Syria’ or ‘interpreter’ Thamsanqa Jantjie Nick Robinson Lara ClarkeBashar al-Assad

19 organisations an Organisation can have properties like ‘address’, ‘website’, and can be notably associated with a person, place or theme

20 places Places can have a latitudes/longitudes and parent features (an administrative district or country for example)

21 themes Themes are the intangible things that we might want to classify our content by: ‘smoking’, ‘unemployment’, ‘health’ health unemployment smoking

22 tagging with a topic :type :about but is this video clip really about the topic of David Cameron?

23 about-ness?

24 tagging with a storyline :type :about :slug “Cameron EU statement” :topic :topic :attribution

25 topics connect storylines

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 automatic aggregation

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 manual curation

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 demo? production tagging with topics and storylines live pilot of storyline tagging in the Midlands


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