COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Recovering implicit information
HLT '86 Proceedings of the workshop on Strategic computing natural language
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
SemEval'07 task 19: frame semantic structure extraction
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Understanding Implicit Entities and Events with Getaruns
ICSC '09 Proceedings of the 2009 IEEE International Conference on Semantic Computing
Beyond NomBank: a study of implicit arguments for nominal predicates
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
SemEval-2010 task 10: Linking events and their participants in discourse
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
SEMAFOR: Frame argument resolution with log-linear models
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
VENSES++: Adapting a deep semantic processing system to the identification of null instantiations
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Casting implicit role linking as an anaphora resolution task
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
LIARc: labeling implicit ARguments in spanish deverbal nominalizations
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
| Hi-index | 0.00 |
In this paper, we address the issue of automatically identifying null instantiated arguments in text. We refer to Fillmore's theory of pragmatically controlled zero anaphora (Fillmore, 1986), which accounts for the phenomenon of omissible arguments using a lexically-based approach, and we propose a strategy for identifying implicit arguments in a text and finding their antecedents, given the overtly expressed semantic roles in the form of frame elements. To this purpose, we primarily rely on linguistic knowledge enriched with role frequency information collected from a training corpus. We evaluate our approach using the test set developed for the SemEval task 10 and we highlight some issues of our approach. Besides, we also point out some open problems related to the task definition and to the general phenomenon of null instantiated arguments, which needs to be better investigated and described in order to be captured from a computational point of view.