par Coeckelbergs, Mathias 
Référence Computational Linguistics in the Netherlands (26: 18 december 2015: Amsterdam)
Publication Non publié, 2015-12-18
Référence Computational Linguistics in the Netherlands (26: 18 december 2015: Amsterdam)
Publication Non publié, 2015-12-18
Communication à un colloque
| Résumé : | In the last decade, Semantic Role Labeling (SRL) has proven to be an important NLP task with many important results. In our exploratory study we show that adding SRL can positively affect sub-sentential alignment between treebanks. We added PropBank semantic roles to a small parallel Dutch-English treebank, and used this information as an additional feature for training the discriminative tree aligner Lingua-Align. We compared conditions with manually added semantics and automatically annotated semantics noting that the former not surprisingly outperforms the latter. If we add a dictionary-based word alignment before our test, adding semantic roles does not improve this score, due to the high baseline. Further exploration has shown that results can be improved when grouping certain PropBank roles into a coarser subdivision. We also experimented with the annotation of several sets of semantic roles in the same sentence, which currently does not yet improve our score, but which already gives a basis for further research. We used the Stockholm Tree Aligner software to visualize the changes in alignment. This allowed us to interpret the changes made by the various configurations of features, and propose additional features and changes for further improvement of alignment. |
