SemEval-2015 Task
A SemEval-2015 Task is a SemEval task associated with the SemEval-2015 Workshop.
- Example(s):
- Counter-Example(s):
- See: Multilingual All-Words Sense Disambiguation and Entity Linking.
References
2015
- http://alt.qcri.org/semeval2015/task13/
- QUOTE: The automatic understanding of the meaning of text has been a major goal of research in computational linguistics and related areas for several decades, with ambitious challenges, such as Machine Reading (Etzioni, 2006) and the quest for knowledge (Schubert, 2006). Two key Natural Language Processing tasks that need to be tackled as steps towards achieving the goal of automatic understanding of text are Word Sense Disambiguation (WSD) and Entity Linking (EL). WSD (Navigli, 2009) is a historical task aimed at explicitly assigning meanings to single-word and [multi-word occurrences within text, a task which is today more alive than ever in the research community. EL (Erbs et al., 2011; Cornolti et al., 2013; Rao et al., 2013) is a more recent task which aims at discovering mentions of entities within a text and linking them to the most suitable entry in a knowledge base. The two main differences between WSD and EL lie in the kind of inventory used, i.e., dictionary vs. encyclopedia, and the assumption that the mention is complete or potentially partial, respectively. For instance, a named entity such as “European Medicines Agency” may be referred to within a text as simply “Medicines Agency”, the meaning of which, however, can be inferred thanks to the context. Notwithstanding these differences, the tasks are pretty similar in nature, in that they both involve the disambiguation of textual fragments according to a reference inventory. However, the research community has hitherto tended to tackle the two tasks separately, often duplicating efforts and solutions.
In contrast to this trend, research in knowledge acquisition is heading towards the seamless integration of encyclopedic and lexicographic knowledge within structured language resources (Hovy et al., 2013), and the main representative of this new direction is undoubtedly BabelNet (http://babelnet.org) (Navigli and Ponzetto, 2012). Therefore these resources seem to provide a common ground for the two tasks of WSD and EL. Only very recently a joint approach, called Babelfy (http://babelfy.org), has been proposed for both the tasks of WSD and EL (Moro et al., 2013).
- QUOTE: The automatic understanding of the meaning of text has been a major goal of research in computational linguistics and related areas for several decades, with ambitious challenges, such as Machine Reading (Etzioni, 2006) and the quest for knowledge (Schubert, 2006). Two key Natural Language Processing tasks that need to be tackled as steps towards achieving the goal of automatic understanding of text are Word Sense Disambiguation (WSD) and Entity Linking (EL). WSD (Navigli, 2009) is a historical task aimed at explicitly assigning meanings to single-word and [multi-word occurrences within text, a task which is today more alive than ever in the research community. EL (Erbs et al., 2011; Cornolti et al., 2013; Rao et al., 2013) is a more recent task which aims at discovering mentions of entities within a text and linking them to the most suitable entry in a knowledge base. The two main differences between WSD and EL lie in the kind of inventory used, i.e., dictionary vs. encyclopedia, and the assumption that the mention is complete or potentially partial, respectively. For instance, a named entity such as “European Medicines Agency” may be referred to within a text as simply “Medicines Agency”, the meaning of which, however, can be inferred thanks to the context. Notwithstanding these differences, the tasks are pretty similar in nature, in that they both involve the disambiguation of textual fragments according to a reference inventory. However, the research community has hitherto tended to tackle the two tasks separately, often duplicating efforts and solutions.
- (Moro & Navigli, 2015) ⇒ Andrea Moro, and Roberto Navigli. (2015). “SemEval-2015 Task 13: Multilingual All-Words Sense Disambiguation and Entity Linking.” In: Proceedings of SemEvel Workshop at NAACL-2015 (SemEval-2015).