Recognizing Phrasal Entailments using Image Groundings

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For this project, I created an effective technique to efficiently extract phrases inspired by bilingual extractions of tree structures. I also designed and evaluated a method to compare sets of images and assess their entailment relation which was also new in the field. Finally, I integrated these innovations in an end-to-end system to measure their impact in the task of Recognizing Textual Entailment, observing a net increase in accuray of 1.2%. My strategy was most successful with nouns, noun phrases and adjectives + nouns; however, it was not effective for most verb phrases and abstract nouns since these phrases cannot be well grounded into images. This worked has been published in JSAI 2017 and EMNLP 2017 which has received 9 citations from other impactful conferences and journals.