Semantic Interpretation of Events in Live Soccer Commentaries
Authors: Anne-Lyse Minard, Manuela Speranza, Bernardo Magnini, Mohammed R. H. Qwaider (Fondazione Bruno Kessler, Università di Brescia, 2016)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In the context of semantic interpretation of live soccer commentaries in Italian, we propose an annotation schema for relevant events and their argument structure, on whose basis we annotated a reference evaluation corpus. We investigated automatic event classification and used Active Learning to reduce the cost of acquiring domain-specific training data.

Introduction
This work focuses on understanding the content of live commentaries of sport games. This form of written reporting has become very popular in recent years, and almost every national Italian online newspaper has a section dedicated to live sport commentaries. Live commentaries have several interesting properties: (i) they are short descriptions of an event written by professionals while the event is happening; their form is much simpler than a full spoken running commentary; (ii) they have a clear and simple structure, typically based on the timing of the sport event; (iii) they are often associated with metadata (e.g. La Roma passa in vantaggio [Roma takes the lead] is associated with the metadata GOAL); (iv) finally, they describe visual scenes, which is relevant to automatic alignment of multimedia content (e.g. align a sequence of frames in a video with the corresponding commentary), a topic of emerging interest in Computational Linguistics (see, for instance, AUTHOR). Our work is part of a larger cross-disciplinary project, Understanding Multimedia Content, currently involving several research groups at FBK. In this paper we first define an annotation framework for the semantic interpretation of online soccer commentaries in Italian (Section sec:annotschema), which includes the detection and classification of relevant events, as well as the identification of their argument structure. Based on this annotation schema, which could also be used for the annotation of tweets or other short online comments, we manually annotated a collection of commentaries in Italian to be used as a gold standard (Section sec:golsstandard). As a first step towards a comprehensive system for automatic interpretation of soccer events we focused on event detection and classification (i.e. event extraction), and used Active Learning to build a training corpus (Section sec:eventExtraction). We show that this procedure is very effective, allowing our system to reach an F1 of 77.25, with considerable savings of annotation time (Section sec:evaluation).

Conclusion
We presented a new annotation framework for the interpretation of online soccer commentaries, as well as the reference annotated corpus we created. We also described our system for event extraction from live soccer commentaries in Italian. It exploits the TextPro-AL Active Learning platform, which allowed us to reach a significant F1 (77.25) in seven working days of a non-expert annotator. The annotation was performed for Italian but the method and the annotation schema we devised can be applied to other languages. The only language dependent component is the feature extractor used by the event detection module. As for ongoing work, we are working at parameter optimization on the Active Learning framework (particularly, we are interested in the relations between the size of the unlabeled dataset, the frequency of the re-training, and the confidence score used by the selection procedure). We also plan to extend the current system by adding the detection of the argument structure of events. We thank Valentino Frasnelli for his contribution, which consisted of manually annotating the data. This work has been partially funded by the Euclip project, in collaboration with Euregio.