Simple Semi-Supervised Training of Part-Of-Speech Taggers
نویسنده
چکیده
Most attempts to train part-of-speech taggers on a mixture of labeled and unlabeled data have failed. In this work stacked learning is used to reduce tagging to a classification task. This simplifies semisupervised training considerably. Our prefered semi-supervised method combines tri-training (Li and Zhou, 2005) and disagreement-based co-training. On the Wall Street Journal, we obtain an error reduction of 4.2% with SVMTool (Gimenez and Marquez, 2004).
منابع مشابه
Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages
Developing natural language processing tools for low-resource languages often requires creating resources from scratch. While a variety of semi-supervised methods exist for training from incomplete data, there are open questions regarding what types of training data should be used and how much is necessary. We discuss a series of experiments designed to shed light on such questions in the conte...
متن کاملTagMiner: A Semisupervised Associative POS Tagger Effective for Resource Poor Languages
We present here, TagMiner, a data mining approach for part-of-speech (POS) tagging, an important Natural language processing (NLP) classification task. It is a semi-supervised associative classification method for POS tagging. Existing methods for building POS taggers require extensive domain and linguistic knowledge and resources. Our method uses combination of a small POS tagged corpus and a ...
متن کاملBuilding part-of-speech Corpora Through Histogram Hopping
This paper are concerned with lowering the cost of producing training resources for part-of-speech taggers. We focus primarily on the resource needs of unsupervised taggers, as these can be trained with simpler resources than their supervised counterparts. We introduce histogram hopping, a new approach for developing the central training resources of unsupervised taggers, and describe a simple ...
متن کاملAdapting taggers to Twitter with not-so-distant supervision
We experiment with using different sources of distant supervision to guide unsupervised and semi-supervised adaptation of part-of-speech (POS) and named entity taggers (NER) to Twitter. We show that a particularly good source of not-so-distant supervision is linked websites. Specifically, with this source of supervision we are able to improve over the state-of-the-art for Twitter POS tagging (8...
متن کاملInvited Talk: Domain-adaptation of Natural Language Processing Tools for RE
Natural language processing tools like part-of-speech taggers and parsers are being used in a variety of applications involving natural language, including RE. Such tools, based on statistical models of language, are learnt via supervised machine learning algorithms from human-annotated data. Due to their dependence on annotated data, which is limited in size and genre, these models have a fall...
متن کامل