Recently, relaxation approaches have been successfully used for MAP inference on NLP problems. In this work we show how to extend the relaxation approach to marginal inference used in conditional likelihood training, posterior decoding, confidence estimation, and other tasks. We evaluate our approach for the case of second-order dependency parsing and observe a tenfold increase in parsing speed...

Natural deduction, which is a method for establishing validity of propositional type arguments, helps develop important reasoning skills and is thus a key ingredient in a course on introductory logic. We present two core components, namely solution generation and practice problem generation, for enabling computer-aided education for this important subject domain. The key enabling technology is ...

This paper reports a critical analysis of the ISO TimeML standard, in the light of several experiences of temporal annotation that were conducted on spoken French. It shows that the norm suffers from weaknesses that should be corrected to fit a larger variety of needs in NLP and in corpus linguistics. We present our proposition of some improvements of the norm before it will be revised by the I...

Natural numerical networks are introduced as a new classification algorithm based on the solution of nonlinear partial differential equations forward-backward diffusion type complete graphs. The proposed natural network is applied to open important environmental and nature conservation task, automated identification protected habitats by using satellite images. In network, forward causes moveme...