This paper, the 5 in a series of biennial progress reports, reviews the activities of the Linguistic Data Consortium with particular emphasis on general trends in the language resource landscape and on changes that distinguish the two years since LDC’s last report at LREC from the preceding 8 years. After providing a perspective on the current landscape of language resources, the paper goes on ...

In this paper we present LXGram, a general purpose grammar for the deep linguistic processing of Portuguese that delivers high precision grammatical analysis and detailed meaning representations. We present the main design features and evaluation results on the grammar’s coverage as well as its ability to produce correct grammatical analyses.

The Linguistic Data Consortium (LDC) has created various annotated linguistic data for a variety of common task evaluation programs and projects to create shared linguistic resources. The majority of these annotated linguistic data were created with highly customized annotation tools developed at LDC. The Annotation Graph Toolkit (AGTK) has been used as a primary infrastructure for annotation t...

Previous studies have shown that object properties are processed faster when they follow properties from the same perceptual modality than properties from different modalities. These findings suggest that language activates sensorimotor processes, which, according to those studies, can only be explained by a modal account of cognition. The current paper shows how a statistical linguistic approa...

This paper explores the potential of machine learning for recognizing and analysing linguistic markers hubris in CEO speech. research is based on three assumptions: associated with potentially destructive leader behaviours; utterances are a way distinguishing between leaders who likely to exhibit such identifying at‐a‐distance using techniques provides reliable, automated scalable method identi...