In this paper, we propose to introduce syntactic classes in a lexicalized dependency formalism. Subcategories of words are organized hierarchically from a general, abstract level (syntactic categories) to a word-specific level (single lexical items). The formalism is parsimonious, and useful for processing. We also sketch a parsing model that uses the hierarchical mixed-grain representation to ...

The typological diversity of the world’s languages poses important challenges for the techniques used in machine translation, syntactic parsing and other areas of natural language processing. Statistical models developed and tuned for English do not necessarily perform well for richly inflected languages, where larger morphological paradigms and more flexible word order gives rise to data spars...

This paper is concerned with whether deep syntactic information can help surface parsing, with a particular focus on empty categories. We design new algorithms to produce dependency trees in which empty elements are allowed, and evaluate the impact of information about empty category on parsing overt elements. Such information is helpful to reduce the approximation error in a structured parsing...

Producing annotated corpora for resource-poor languages can be prohibitively expensive, while obtaining parallel, unannotated corpora may be more easily achieved. We propose a method of augmenting a discriminative dependency parser using syntactic projection information. This modification will allow the parser to take advantage of unannotated parallel corpora where high-quality automatic annota...

Almost all automatic semantic role labeling (SRL) systems rely on a preliminary parsing step that derives a syntactic structure from the sentence being analyzed. This makes the choice of syntactic representation an essential design decision. In this paper, we study the influence of syntactic representation on the performance of SRL systems. Specifically, we compare constituent-based and depende...

The prosody of speech is closely related to syntactic structure of the spoken sentence, and thus analysis models that jointly consider these two types of information are promising. However, manual annotation of syntactic information and prosodic information such as pauses is laborious, and thus it can be difficult to obtain sufficient data to train such joint models. In this paper, we tackle th...

We present a new toolkit NiuParser for Chinese syntactic and semantic analysis. It can handle a wide range of Natural Language Processing (NLP) tasks in Chinese, including word segmentation, partof-speech tagging, named entity recognition, chunking, constituent parsing, dependency parsing, and semantic role labeling. The NiuParser system runs fast and shows state-of-the-art performance on sever...