1. REACTION REACTION Workshop 2011.01.06 Task 2 – Progress Report & Plans Lisbon, PT and Austin, TX Mário J. Silva University of Lisbon, Portugal

2. REACTION Information Discovery Relationship extraction techniques to support information discovery in journalists activities Entity Ranking: finding the relevant entities for a given topic Entity Distillation: finding relevant resources for a given entity Attribute Selection: finding a list of key aspects to compare and differentiate a given set of entities

3. REACTION Annotation Socrates reuniu hoje em Braga com Mesquita Machado e Firmino Marques NER Mapping Socrates reuniu hoje em Braga com Mesquita Machado e Firmino Marques Annotated Corpus

4. REACTION Analysis Voos da CIA em Portugal Entity Ranking Annotated Corpus 1.Luís Amado 2.José Socrates (Power:1) Entity Distillation XVII Governo Constitucional (Power:20) WikiLeaks Attribute Selection http://pt.wikipedia.org/wiki/Luís_Amado Ontology Extension

5. REACTION First Approach NER – REMBRANDT (Reconhecimento de Entidades Mencionadas Baseado em Relações e ANálise Detalhada do Texto) Mapping (Classification or Grounding) – String Matching Methods – Ontologies: POWER (task 1); GeoNetPT; Yahoo! GeoPlanet

6. REACTION

8. Socrates reuniu hoje em Braga com Mesquita Machado e Firmino Marques.

9. REACTION Prototype: First Release April 2011 To be used in the Web Applications course unit project Whats missing? – Mapping – Interface – Evaluation Precision and recall Gold standard (Task 1)

10. REACTION Prototype: Second Release August 2011 Evaluate and Analyze First Prototype Results Improved NER and Mapping – Using machine learning Conditional Random Fields – Information Content FiGO

11. REACTION Prototype: Third Release December 2011 Containing Modules for: – Entity Ranking – Entity Distillation – Attribute Selection – Ontology Extension Participate in TREC (Entity Track) – http://ilps.science.uva.nl/trec-entity/ http://ilps.science.uva.nl/trec-entity/

12. REACTION Prototype: Fourth Release August 2012 Containing Modules for: – Opinion mining Using machine learning to Detect and classify opinionated text Targeting the identified entities and topics