This paper describes our system to carry out the joint parsing of syntactic and semantic dependencies for our participation in the shared task of CoNLL-2008. We illustrate that both syntactic parsing and semantic parsing can be transformed into a word-pair classification problem and implemented as a single-stage system with the aid of maximum entropy modeling. Our system ranks the fourth in the...

We investigate the effect of viscous dissipation on the thermal transport characteristics of heat and its consequence in terms of the entropy-generation rate in a circular Couette flow. We consider the flow of a Newtonian fluid through a narrow annular space between two asymmetrically-heated concentric micro-cylinders where the inner cylinder is rotating at a constant speed. Employing an analyt...

As part of its description of lexico-semantic predicate frames or conceptual structures, the FrameNet project defines a set of semantic roles specific to the core predicate of a sentence. Recently, researchers have tried to automatically produce semantic interpretations of sentences using this information. Building on prior work, we describe a new method to perform such interpretations. We defi...

In this paper, we propose an approach for inferring semantic role using subcategorization frames and maximum entropy model. Our approach aims to use the sub-categorization information of the verb to label the mandatory arguments of the verb in various possible ways. The ambiguity between the assignment of roles to mandatory arguments is resolved using the maximum entropy model. The unlabelled m...

Many statistical properties are determined not by the probabilities of the possible outcomes, but just by the multiset of these probabilities. We estimate this probability multiset from an observed data sample. Akin to standard maximum likelihood, which maximizes the probability of the observed outcomes, we propose profile maximum likelihood (PML), which maximizes the probability of the observe...

There are two entropy-based methods to deal with linear inverse problems, which we shall call the ordinary method of maximum entropy (OME) and the method of maximum entropy in the mean (MEM). Not only does MEM use OME as a stepping stone, it also allows for greater generality. First, because it allows to include convex constraints in a natural way, and second, because it allows to incorporate a...

The maximum entropy method has recently been successfully introduced to a variety of natural language applications. In each of these applications, however, the power of the maximum entropy method is achieved at the cost of a considerable increase in computational requirements. In this paper we present a technique, closely related to the classical cluster expansion from statistical mechanics , f...

A new algorithm for computing the maximum entropy ranking over models is presented. The algorithm handles arbitrary sets of proposi-tional defaults with associated strength assignments and succeeds whenever the set satisses a robustness condition. Failure of this condition implies the problem may not be suuciently speciied for a unique solution to exist. This work extends the applicability of t...

Based on the maximum entropy (MaxEnt) principle for a generalized entropy functional and the conjugate representations introduced by Zhang, we have reformulated the method of information geometry. For a set of conjugate representations, the associated escort expectation is naturally introduced and characterized by the generalized score function which has zero-escort expectation. Furthermore, we...

This paper shows results of recovering punctuation over speech transcriptions for a Portuguese broadcast news corpus. The approach is based on maximum entropy models and uses word, part-of-speech, time and speaker information. The contribution of each type of feature is analyzed individually. Separate results for each focus condition are given, making it possible to analyze the differences of p...