Candidates using ir methods augmented with ontologies

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Unformatted text preview: a seman+c representa+on of the query •  Times, dates, loca+ons, en++es, numeric quan++es •  Map from this seman+cs to query structured data or resources •  •  •  •  13 Geospa+al databases Ontologies (Wikipedia infoboxes, dbPedia, WordNet, Yago) Restaurant review sources and reserva+on services Scien+fic databases Dan Jurafsky Hybrid approaches (IBM Watson) •  Build a shallow seman+c representa+on of the query •  Generate answer candidates using IR methods •  Augmented with ontologies and semi ­structured data •  Score each candidate using richer knowledge sources •  Geospa+al databases •  Temporal reasoning •  Taxonomical classifica+on 14 Question Answering What is Ques+on Answering? Question Answering Answer Types and Query Formula+on Dan Jurafsky Factoid Q/A Document Document Document Document Document Document Answer Indexing Passage Retrieval Question Processing Question Query Formulation Answer Type Detection 17 Document Retrieval Docume Docume nt Docume nt Docume nt Docume nt Relevant nt Docs Passage Retrieval passages Answer Processing Dan Jurafsky Ques%on Processing Things to extract from the ques%on •  Answer Type Detec+on •  Decide the named en%ty type (person, place) of the answer •  Query Formula+on •  Choose query keyw...
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