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NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud

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NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud

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Talk "NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud" event during LDOW'12 (WWW'12), Lyon, France

Talk "NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud" event during LDOW'12 (WWW'12), Lyon, France

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NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud

  1. 1. s NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud Giuseppe Rizzo and Raphaël Troncy EURECOM, France Sebastian Hellmann and Martin Bruemmer Universität Leipzig, Germany
  2. 2. What is a Named Entity recognition task? A task that aims to locate and classify the name of a person or an organization, a location, a brand, a product, a numeric expression including time, date, money and percent in a textual document 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 2/15
  3. 3. NER tools  Standalone software GATE Stanford CoreNLP Temis  Web APIs 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 3/15
  4. 4. Factual comparison of 10 Web NER tools Alchemy DBpedia Evri Extractiv Lupedia Open Saplo Wikimeta Yahoo! Zemanta API Spotlight Calais Language EN,FR, EN EN, EN EN,FR, EN,FR EN, EN,FR EN EN GR,IT, GR* IT IT SP SW SP PT,RU, PT* SP,SW SP* Granularity OEN OEN OED OEN OEN OEN OED OEN OEN OED Entity N/A char N/A word range of char N/A POS range N/A position offset offset chars offset offset of chars Classification Alchemy DBpedia Evri DBpedia DBpedia Open N/A ESTER Yahoo FreeBase schema FreeBase LinkedM Calais Scema.or DB g Number of 324 320 5 34 319 95 5 7 13 81 classes Response JSON HTML HTM HTML HTML JSON JSON JSON JSON XML Format MicroF JSON L JSON JSON MicroF XML XML JSON XML RDF JSO RDF RDFa ormat RDF RDF XML N XML XML RDF Quota 30000 unl 3000 3000 unl 50000 1333 unl 5000 10000 (calls/day) 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 4/15
  5. 5. What is NERD? ontology1 REST API2 UI3 The NERD ontology has been integrated in the NIF project, a EU FP7 in the context of the LOD2: Creating Knowledge out of Interlinked Data 1 http://nerd.eurecom.fr/ontology 2 http://nerd.eurecom.fr/api/application.wadl 3 http://nerd.eurecom.fr 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 5/15
  6. 6. NERD Ontology Aligned the taxonomies used by the extractors 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 6/15
  7. 7. NERD type Occurrence Building the NERD Ontology Person 10 Organization 10 Country 6 Company 6 Location 6 Continent 5 City 5 RadioStation 5 Album 5 Product 5 ... ... 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 7/15
  8. 8. Ontology alignment validation 5 TED talks 1000 NYT news articles 217 WWW2011 abstracts 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 8/15
  9. 9. Integration  Different outputs for the NLP tools (Standalone and Web APIs) OpenCalais DBpedia Spotlight "_type": "Organization", "@URI": "http://dbpedia.org/resource/DBpedia", “name": "North Atlantic Treaty Organization", "@types": "DBpedia:Software,DBpedia:Work” "organizationtype": "governmental civilian", "@surfaceForm": "dbpedia", "nationality": "N/A", "@offset": "0", "_typeReference": "@support": "11", http://s.opencalais.com/1/type/em/e/Organization", "@similarityScore": "0.2387271374464035", ... …  For integration or reuse manual effort is needed  time consuming  difficult to track definitions  NERD creates a sharable JSON/RDF annotation output 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 9/15
  10. 10. NERD REST API “entities” : [{ “entity”: “W3C” , “type”: “Organization” , “uri”: "http://dbpedia.org/page/W3C", JSON “nerdType”: "http://nerd.eurecom.fr/ontology#Organization", “startChar”: 30, “endChar”: 32, /document/{idDocument} “confidence”: 1, /user/{idUser} GET, “relevance”: 0.5 POST, }] /annotation/{extractor} /extraction/{idExtraction} PUT, /evaluation DELETE ... RDF 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 10/15
  11. 11. Textual annotation Let's consider the URI: http://www.w3.org/DesignIssues/LinkedData.html The Semantic Web isn't just about putting data on the web. It is about making links, so that a person or machine can explore the web of data. With linked data, when you have some of it, you can find other, related, data.…. All the above plus, Use open standards from W3C (RDF and SPARQL) to identify things, so that people can point at your stuff ... entities: { … [entity: W3C, startChar: 23107, endChar: 23110], … } 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 11/15
  12. 12. NERD meets NIF Model documents through a set of strings deferencable within the Web : offset_23107_ 23110 a str:String ; str:referenceContext :offset_0_26546 . Map string to entity : offset_23107_ 23110 sso:oen dbpedia:W3C . Classification dbpedia:W3C rdf:type nerd:Organization . 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 12/15
  13. 13. NERD User Interface 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 13/15
  14. 14. Conclusions and perspectives NERD UI and REST API unified interface for extracting NEs from various type of texts NERD ontology common schema for entity classification NERD & NIF lift the extraction annotation results to the LOD cloud Systematic comparison for the NE extraction and classification tasks: ETAPE corpus CoNLL 2003 corpus Combining several extractions to improve the strengths of a single tool 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 14/15
  15. 15. Thanks for your time and your attention http://nerd.eurecom.fr @giusepperizzo @rtroncy #nerd http://www.slideshare.net/giusepperizzo 16/04/2012 5th Workshop on Linked Data on the Web (LDOW2012) 15/15

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