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Task 2: Ex trinsic Evaluation. Vasile Rus , Wei Chen, Pascal Kuyten , Ron Artstein, Elnaz Nouri. New modality. Generate questions from pictures Provide text/metadata description as a seed for QG systems (to be dispensed with in the future) Users/evaluators only see the picture
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Task 2: Extrinsic Evaluation VasileRus, Wei Chen, Pascal Kuyten, Ron Artstein, ElnazNouri
New modality • Generate questions from pictures • Provide text/metadata description as a seed for QG systems (to be dispensed with in the future) • Users/evaluators only see the picture • Answer = region in image; users interact graphically
Users evaluate each other • Users provide answers to generated questions • Users evaluate answers from other users • http://anawiki.essex.ac.uk/phrasedetectives/
Evaluate Q-A pairs • Motivate children to answer questions • Correct answer = plant seed in virtual garden • http://pbskids.org/arthur/games/groovygarden/groovygarden.html • Systems provide questions and answers • Perhaps questions, answers and distractors? • Rate of correct responses = quality of q-a pair
Guess who • User chooses a picture element • System asks yes/no questions • User can answer yes, no, don’t understand • Evaluates question answerability • Goal: best strategy to get to user’s choice • Metric: number of steps • Question formulation might be trivial • Hard part is deciding what to ask • Build model of user inentions • Create taxonomy on the fly? In a short time?
What systems should win • QG has two essential components • What to ask • How to ask it • (Optional: answer your question) • Either what or how should be non-trivial • Winner = the most templates: is that good?