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![FREME – General overview. Version June 2015 WWW.FREME-PROJECT.EU 12
INTEGRATING SEMANTIC ENRICHMENT INTO MULTILINGUAL
CONTENT IN TRANSLATION AND LOCALISATION
• Enriching content with machine readable information – represented as JSON-LD
◦ Input: “Welcome to Berlin … Marlene Dietrich!”
◦ Output:
[
{
"@id": "dbpedia:Marlene_Dietrich",
"@type": "person",
"born": "1901-12-27"
}
]
May be basis e.g. for further processing, e.g.
multilingual generation:
• “… born 1901”
• “… geboren 1901”
• “…１９０１年生まれ”
• …](https://image.slidesharecdn.com/freme-general-overview-version-june-2015-150626074940-lva1-app6892/75/Freme-general-overview-version-june-2015-12-2048.jpg)
Uploaded byFREMEProjectH2020
Freme general-overview-version-june-2015
The FREME project is a two-year Horizon 2020 project that aims to bridge language and data technologies. It involves industry partners leading four business cases around digital content and linked data. The project will develop a set of interfaces for language and data technologies to allow users like content authors and developers to easily integrate these technologies. The interfaces will be designed based on the needs of the business cases in domains like publishing, translation, agriculture, and personalization.
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- 1. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 1 Co-funded by the Horizon 2020 Framework Programme of the European Union Grant Agreement Number 644771 VERSION: JUNE 2015 Presented on behalf of the FREME Consortium FREME – GENERAL OVERVIEW www.freme-project.eu
- 2. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 2 THE FREME PROJECT • Two year H2020 Innovation action; start February 2015 • Industry partners leading four business cases around digital content and (linked) data • Technology development bridging language and data • Outreach and business modelling demonstrating monetization of the multilingual data value chain
- 3. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 3 CHALLENGE AND OPPORTUNITY: BIG DATA IS GROWING ACROSS LANGUAGES, SECTORS AND DOMAINS • BC: Digital publishing • BC: Translation and localisation • BC: Agriculture and food domain data • BC: Web site personalisation Agriculture metadata, user content, news content, … WHAT LIES AHEAD FOR SEVERAL INDUSTRIES? SEE THE FREME BUSINESS CASES EN ES JA, ZH, ... AR
- 4. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 4 CURRENT STATE OF SOLUTIONS Machine translation, terminology annotation, ... Linked data creation & processing GAPS THAT HINDER BUSINESS: • Plethora of formats • Adaptability and platform dependency • Language coverage • Usability “The right tool for the right person in given and new enterprises”: technology influences job profiles
- 5. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 5 FREME TO THE RESCUE: ENRICHING DIGITAL CONTENT Machine translation, terminology annotation, ... Linked data creation & processing LT and LD as first class citizens on the Web A SET OF INTERFACES* - DESIGN DRIVEN BY BUSINESS CASES LT and LD for various user types: (application) developer, content architect, content author, … * Graphical interfaces * Software Interfaces
- 6. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 6
- 7. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 7 EACH SERVICE IN ONE SENTENCE • e-Translation: “Translate from Dutch to English” • e-Terminology: “Add terminology annotations” • e-Entity: “Identify unique entities” • e-Link: “Add information from (linked open) data sources” • e-Publishing: “Publish as digital book content” • e-Internationalisation: “Use standardised metadata for multilingual content production” A KEY ASPECT FREME: FREME will allow to combine data and language technologies via adequate software interfaces (APIs) and graphical user interfaces (GUIs)
- 8. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 8 AUTHORING AND PUBLISHING MULTILINGUALLY AND SEMANTICALLY ENRICHED EBOOKS • Challenge ◦ Moving to digital publishing workflows leads to high costs. Added value beyond the content itself is needed. • Solution ◦ Easy to integrate solutions, based on standardised interfaces for software components and authors, responding to usability requirements
- 9. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 9 AUTHORING AND PUBLISHING MULTILINGUALLY AND SEMANTICALLY ENRICHED EBOOKS • Example: Integration into ePub editing mode of oXygen XML Editor e-Entity: annotate named entities
- 10. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 10 INTEGRATING SEMANTIC ENRICHMENT INTO MULTILINGUAL CONTENT IN TRANSLATION AND LOCALISATION • Challenge ◦ Localisation service providers are under pressure: more speed, better quality, lower payment rates per translation outcomes. LSPs need to offer additional services, going beyond translation • Solution ◦ Allow translators to work with linked data sources during the translation process, to add additional information to the translated content.
- 11. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 11 INTEGRATING SEMANTIC ENRICHMENT INTO MULTILINGUAL CONTENT IN TRANSLATION AND LOCALISATION • Example: Integration into XLIFF 2.0 editing mode of oXygen XML Editor • Combination of services ◦ e-Entity: annotate named entities ◦ e-Link: fetch additional information from a linked data source like dbpedia, specific to the type of entities (places, persons, …)
- 12. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 12 INTEGRATING SEMANTIC ENRICHMENT INTO MULTILINGUAL CONTENT IN TRANSLATION AND LOCALISATION • Enriching content with machine readable information – represented as JSON-LD ◦ Input: “Welcome to Berlin … Marlene Dietrich!” ◦ Output: [ { "@id": "dbpedia:Marlene_Dietrich", "@type": "person", "born": "1901-12-27" } ] May be basis e.g. for further processing, e.g. multilingual generation: • “… born 1901” • “… geboren 1901” • “…１９０１年生まれ” • …
- 13. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 13 ENHANCING THE CROSS LANGUAGE SHARING AND ACCESS TO OPEN AGRICULTURAL AND FOOD DATA • Challenge ◦ Content metadata is not available in multiple languages, needs to be curated manually, and the metadata is not linked to external data sources. • Solution ◦ Via FREME, make metadata available in several languages ◦ Easy data discovery for users with different linguistic profiles ◦ Allow to reach out to new markets
- 14. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 14 FREME-EMPOWERED PERSONALISED CONTENT RECOMMENDATIONS • Challenge ◦ Personalised content recommendations for content rich websites help to increase engagement of users on a website. Current solutions focuses on English web sites. • Solution ◦ Using FREME, content recommendation will be provided in several languages ◦ The e-Services e-Entity and e-Translation will help to identify user relevant items in Web content
- 15. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 15 WANT TO TRY THINGS OUT? • Go to http://api.freme-project.eu/doc/0.1/ • Check out API demo calls • Time line for next prototypes ◦ 0.2: mid July ◦ 0.3: end of August ◦ Feedback to GitHub: https://github.com/freme-project - Will be made public repro mid July
- 16. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 16 NEXT STEPS FOR FREME Creating & updating prototypes of e-Services Agile approach: gathering feedback from business cases feeds implementations Potential input to standardisation of the open Web platform: ease access to data (sources + technologies) and language technologies for various user types Learn more at www.freme-project.eu Get input from users outside the FREME consortium
- 17. FREME – Generaloverview. Version June 2015 WWW.FREME-PROJECT.EU 17 CONTACTS On behalf of the FREME consortium E-mail: info@freme-project.eu CONSORTIUM
Editor's Notes
- #3 This slide probably needs no visualization.
- #4 BC 1 “Digital publishing”: Digital content itself is exploding and is loosing value BC 2 “Translation and Localisation”: Demand for speed and quality is increasing, prices are going down BC 3 “Agriculture and food data”: Discovery of data is difficult due to missing multilingual metadata BC 4 “Web site personalisation”: solutions are focusing on English speaking market
- #5 Robust language technologies Machine translation, terminology extraction & annotation Robust linked data (LD) technologies Entity annotation, linking to data sources More and more platforms as silos that allow to deploy certain parts of these technology stacks GAPS that hinder businesses: No easy to use interfaces to LT and LD tooling Plethora of formats to process Adaptability and scalability of solutions Usability: “Give the adequate tool to the right person”
- #7 e-Translation: “Translate from Dutch to English” e-Terminology: “Add terminology annotations” e-Entity: “Identify unique entities” e-Link: “Add information from (linked open) data sources” e-Publishing: “Publish as digital book content” e-Internationalisation: “Use standardised metadata for multilingual content production” A KEY ASPECT FREME: FREME will allow to combine data and language technologies via adequate software interfaces (APIs) and graphical user interfaces (GUIs)
- #17 This also won‘t need visualizations I think
- #18 Back Page #1 Social network icons refer to speaker (he/she has to link his/her accounts)