We present a novel method for predicting inflected word forms for generating morphologically rich languages in machine translation. We utilize a rich set of syntactic and morphol...
We present an implemented system for the resolution of it, this, and that in transcribed multi-party dialog. The system handles NP-anaphoric as well as discoursedeictic anaphors, ...
We extend the classical single-task active learning (AL) approach. In the multi-task active learning (MTAL) paradigm, we select examples for several annotation tasks rather than f...
Roi Reichart, Katrin Tomanek, Udo Hahn, Ari Rappop...
Identification of transliterated names is a particularly difficult task of Named Entity Recognition (NER), especially in the Chinese context. Of all possible variations of trans...
Parse-tree paths are commonly used to incorporate information from syntactic parses into NLP systems. These systems typically treat the paths as atomic (or nearly atomic) features...
We propose the use of regular tree grammars (RTGs) as a formalism for the underspecified processing of scope ambiguities. By applying standard results on RTGs, we obtain a novel a...
We present a novel framework that combines strengths from surface syntactic parsing and deep syntactic parsing to increase deep parsing accuracy, specifically by combining depend...
In adding syntax to statistical MT, there is a tradeoff between taking advantage of linguistic analysis, versus allowing the model to exploit linguistically unmotivated mappings l...
We describe an open-source toolkit for statistical machine translation whose novel contributions are (a) support for linguistically motivated factors, (b) confusion network decodi...
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris ...
We propose an automatic machine translation (MT) evaluation metric that calculates a similarity score (based on precision and recall) of a pair of sentences. Unlike most metrics, ...