This paper describes a systematic investigation of the extent to which the part of speech of words can be identified from their prefixes and suffixes. The results indicate that it is possible to determine, with 95 per cent accuracy, the inclusive part of speech of an affixed word from a consideration of its prefixes, suffixes, and length. By "inclusive" parts of speech we mean a string that wil...

Treating shallow parsing as part-of-speech tagging yields results comparable with other, more elaborate approaches. Using the CoNLL 2000 training and testing material, our best model had an accuracy of 94.88%, with an overall FB1 score of 91.94%. The individual FB1 scores for NPs were 92.19%, VPs 92.70% and PPs 96.69%.

Most current dependency parsers presuppose that input words have been morphologically disambiguated using a part-of-speech tagger before parsing begins. We present a transitionbased system for joint part-of-speech tagging and labeled dependency parsing with nonprojective trees. Experimental evaluation on Chinese, Czech, English and German shows consistent improvements in both tagging and parsin...

This is a pilot study which aims at the design of a Chinese morphological analyzer which is in state to predict the syntactic and semantic properties of nominal, verbal and adjectival compounds. Morphological structures of compound words contain the essential information of knowing their syntactic and semantic characteristics. In particular, morphological analysis is a primary step for predicti...

The use of distance functions in order to determine nearest instance class at Memory Based Learning methods may be crucial when there are no exact matchings. We add relative information over unknown feature values to improve the information extract on the training instances. An experiment was carried out for Spanish Part-Of-Speech tagging of unknown words nding a better performance with our mod...

We investigate the problem of unsupervised part-of-speech tagging when raw parallel data is available in a large number of languages. Patterns of ambiguity vary greatly across languages and therefore even unannotated multilingual data can serve as a learning signal. We propose a non-parametric Bayesian model that connects related tagging decisions across languages through the use of multilingua...

We address the problem of part-of-speech tagging for English data from the popular microblogging service Twitter. We develop a tagset, annotate data, develop features, and report tagging results nearing 90% accuracy. The data and tools have been made available to the research community with the goal of enabling richer text analysis of Twitter and related social media data sets.

Part-of-speech tagging (POS-tagging) of spoken data requires different means of annotation than POS-tagging of written and edited texts. In order to capture the features of German spoken language, a distinct tagset is needed to respond to the kinds of elements which only occur in speech. In order to create such a coherent tagset the most prominent phenomena of spoken language need to be analyze...

Two online research tools are presented in this paper: PermA, a general-purpose string aligner which can for example be used for grapheme-to-phoneme and phonemeto-phoneme alignment, and Balloon, a text processing toolkit for German and English providing components for part-of-speech tagging, morphological analyses, and grapheme-to-phoneme conversion including syllabification and word-stress ass...