Semantic Understanding of Professional Soccer Commentaries
By Hannaneh Hajishirzi, Mohammad Rastegari, Ali Farhadi, Jessica K. Hodgins. 2012
10 citations recorded by the source corpus.
This paper presents a novel approach to the problem of semantic parsing via learning the correspondences between complex sentences and rich sets of events. 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.
Subfields: Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Natural Language Processing
- Hannaneh Hajishirzi
- Ashish Sabharwal
- Peter Clark
- Ali Farhadi
- Jonathan Berant
- Oren Etzioni
- Tushar Khot
- Luke S. Zettlemoyer
Citations in the corpus
- Parsing Algebraic Word Problems into Equations (2015, background): “More closely related is work on language grounding, whose goal is the interpretation of a sentence in the context of a world representation (Branavan et al., 2009; Liang et al., 2009; Chen et al., 2010; Bordes et al., 2010; Feng and Lapata, 2010; Hajishirzi et al., 2011; Matuszek et al., 2012; Hajis”
- Multi-Resolution Language Grounding with Weak Supervision (2014, methodology): “The language employed in soccer commentaries is difficult to ground due to its dense information structure, novel vocabulary and word senses, and colorful, non-traditional syntax.”