Hola!
Us recordem que avui dimecres 8 de juliol tenim programat un seminari del TALP a càrrec de Xavier Lluís, a l'aula S208 de l'Edifici Omega del Campus Nord de la UPC. El seminari serà un assaig de la defensa de tesi que tindrà lloc el proper dilluns 13 de juliol a les 11:00.
L'hora d'inici del seminari seran les 11:00.
Aquests són els detalls del seminari:
| Títol | Joint Parsing of Syntactic and Semantic Dependencies |
|---|---|
| Ponent | Xavier Lluís |
| Lloc | Omega-S208 Campus Nord - UPC |
| Dia | 8 Juliol 2015 |
| Horari | 11:00h - Presentació |
| Abstract |
Syntactic Dependency Parsing and Semantic Role Labeling (SRL) are two main problems in Natural Language Understanding. Both tasks are closely related and can be regarded as parsing on top of a given sequence. In the data-driven approach context, these tasks are typically addressed sequentially by a pipeline of classifiers. A syntactic parser is run in the first stage, and then given the predicates, the semantic roles are identified and classified (Gildea and Jurafsky, 2002). An appealing and largely unexplored idea is to jointly process syntactic dependencies and semantic roles. A joint process could capture some interactions that pipeline systems are unable to model. We expect joint models to improve on syntax based on semantic cues and also the reverse. Despite this potential advantage and the interest in joint processing stimulated by the CoNLL-2008 and 2009 Shared Tasks (Surdeanu et al., 2008; Hajic et al., 2009), very few joint models have been proposed to date, few have achieved attention and fewer have obtained competitive results. This thesis presents three contributions on this topic. The first contribution is to frame semantic role labeling as a linear assignment task. The second contribution is a joint model that combines syntactic parsing and SRL (Lluís et al., 2013). The third contribution is a model that finds semantic roles together with syntactic paths linking predicates and arguments (Lluís et al., 2014). |
Fins aviat!
Pranava i Xavi