A corpus-based analysis of argument realization by preposition structures
Natural Language Engineering
Automatic Frame Extraction from Sentences
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
CLR: Linking events and their participants in discourse using a comprehensive FrameNet dictionary
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Chinese frame identification using T-CRF model
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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In SemEval-2007, CL Research participated in the task for Frame Semantic Structure Extraction. Participation in this task was used as the vehicle for efforts to integrate and exploit FrameNet in a comprehensive text processing system. In particular, this involved steps to build a FrameNet dictionary with CL Research's DIMAP dictionary software and to use this dictionary (along with its semantic network processing capabilities) in processing text into XML representations. Implementation of the entire integrated package is only in its initial stages and was used to make only a bare submission of frame identification. On this task, over all texts, a recall of 0.372, a precision of 0.553, and an F-score of 0.445 were achieved. Considering only targets included in the DIMAP FrameNet dictionary, the overall F-score is 0.605. These results, competitive with the top scoring system, support continued attempts at a dictionary-based approach to frame structure extraction.