Semantic Understanding of Professional Soccer Commentaries

Hannaneh Hajishirzi, Mohammad Rastegari, Ali Farhadi, Jessica Hodgins

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Abstract:

This paper presents a novel approach to the problem of semantic parsing via learning the correspondences between complex sentences and rich sets of event. Our main intuition is that correct correspondences tend to occur more frequently. Our model benefits from a discriminative notion of similarity to learn the correspondence between sentence and an event and a ranking machinery that scores the popularity of each correspondence. Our method can discover a group of events (called macro-events) that best describes a sentence. We evaluate our method on our novel dataset of professional soccer commentaries. The empirical results show that our method significantly outperforms the state-of-the-art. .

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Paper:

Hannaneh Hajishirzi, Mohammad Rastegari, Ali Farhadi, Jessica Hodgins. Semantic Understanding of Professional Soccer Commentaries. UAI, 2012. [PDF][bibtex]

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Dataset:

Dataset for proffesional soccer comentaries is available here and a MATLAB wrapper for feature extraction is available here.

The above figure shows examples of sentences in the commentaries with corresponding buckets of events. The correct correspondences in each bucket are marked with arrows. .

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