Summary of the paper
| Title | Using C5.0 and Exhaustive Search for Boosting Frame-Semantic Parsing Accuracy |
|---|---|
| Authors | Guntis Barzdins, Didzis Gosko, Laura Rituma and Peteris Paikens |
| Abstract | Frame-semantic parsing is a kind of automatic semantic role labeling performed according to the FrameNet paradigm. The paper reports a novel approach for boosting frame-semantic parsing accuracy through the use of the C5.0 decision tree classifier, a commercial version of the popular C4.5 decision tree classifier, and manual rule enhancement. Additionally, the possibility to replace C5.0 by an exhaustive search based algorithm (nicknamed C6.0) is described, leading to even higher frame-semantic parsing accuracy at the expense of slightly increased training time. The described approach is particularly efficient for languages with small FrameNet annotated corpora as it is for Latvian, which is used for illustration. Frame-semantic parsing accuracy achieved for Latvian through the C6.0 algorithm is on par with the state-of-the-art English frame-semantic parsers. The paper includes also a frame-semantic parsing use-case for extracting structured information from unstructured newswire texts, sometimes referred to as bridging of the semantic gap. |
| Topics | Semantics, Statistical and Machine Learning Methods |
Full paper  |
Using C5.0 and Exhaustive Search for Boosting Frame-Semantic Parsing Accuracy |
| Bibtex | @InProceedings{BARZDINS14.515, author = {Guntis Barzdins and Didzis Gosko and Laura Rituma and Peteris Paikens}, title = {Using C5.0 and Exhaustive Search for Boosting Frame-Semantic Parsing Accuracy}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |