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Semantic Entailment

Semantic Entailment. Nathaniel Story Ginger Buckbee Greg Lorge Billy Dean . What is it?. Given sentence A, can you infer sentence B?. Challenges. Paraphrasing Negation Pre-Suppositions World Knowledge Juiciness . Paraphrasing Example. “There is a cat on the table.”

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Semantic Entailment

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  1. Semantic Entailment Nathaniel Story Ginger Buckbee Greg Lorge Billy Dean

  2. What is it? Given sentence A, can you infer sentence B?

  3. Challenges • Paraphrasing • Negation • Pre-Suppositions • World Knowledge • Juiciness

  4. Paraphrasing Example • “There is a cat on the table.” • “A cat is on the table.” • Different structurally, but infers same meaning

  5. Negation • “I am lazy” • “I am not lazy” • “I’m not unhappy” (Double negation) • “I’m happy” • “It’s not unnecessary” • “It’s necessary”

  6. Pre-Suppositions • “Bob doesn’t think it’s raining” • “Bob doesn’t know it’s raining” • Conversational Pragmatics • Contextual knowledge

  7. World Knowledge • “Japan is the only country that currently has an emperor.” • “Columbia doesn’t have an emperor.” • First sentence entails second, but you need to know that Columbia is a country.

  8. Approach • Tools: • Stemmer • Parser from Dan Bikel’s site • MALLET (maxEnt classifier) • Wordnet (synset) • Focusing on Comparable Document task • Start with simple features like word matching, synonym matching • Add in more complicated functions like phrase structure comparisons • Test the system out, see how it works. Continue adding features to improve performance.

  9. Data • Recognizing Textual Entailment Challenge (RTE) training data set • Training set is labeled • Best data set as was used in the European Competition

  10. Evaluation • International Competition • Best ≈ 60% accuracy • Strive for >52% accuracy • Comparing against annotated test set • Improvement: Print out incorrect ones, then look for mistakes.

  11. The End Questions?

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