We present a simple, two-steps supervised strategy for the identification and classification of thematic roles in natural language texts. We employ no external source of informat...
We present the results of a systematic study of the contextual gain hypothesis for image classification. This hypothesis relates the traditional strategy of direct visual classi...
A number of studies have presented machine-learning approaches to semantic role labeling with availability of corpora such as FrameNet and PropBank. These corpora define the seman...
We present a new ensemble method that uses Entropy Guided Transformation Learning (ETL) as the base learner. The proposed approach, ETL Committee, combines the main ideas of Baggin...
This paper presents a semantic parsing approach for non domain-specific texts. Semantic parsing is one of the major bottlenecks of Natural Language Understanding (NLU) systems and...