MBT: A Memory-Based Part of Speech Tagger-Generator. We introduce a memory-based approach to part of speech tagging. Memory-based learning is a form of supervised learning based on similarity-based reasoning. The part of speech tag of a word in a particular context is extrapolated from the most similar cases held in memory. Supervised learning approaches are useful when a tagged corpus is available as an example of the desired output of the tagger. Based on such a corpus, the tagger-generator automatically builds a tagger which is able to tag new text the same way, diminishing development time for the construction of a tagger considerably. Memory-based tagging shares this advantage with other statistical or machine learning approaches. Additional advantages specific to a memory-based approach include (i) the relatively small tagged corpus size sufficient for training, (ii) incremental learning, (iii) explanation capabilities, (iv) flexible integration of information in case representations, (v) its non-parametric nature, (vi) reasonably good results on unknown words without morphological analysis, and (vii) fast learning and tagging. In this paper we show that a large-scale application of the memory-based approach is feasible: we obtain a tagging accuracy that is on a par with that of known statistical approaches, and with attractive space and time complexity properties when using IGTree, a tree-based formalism for indexing and searching huge case bases. The use of IGTree has as additional advantage that optimal context size for disambiguation is dynamically computed.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Tait, John I. (ed.): Charting a new course: Natural language processing and information retrieval. Essays in honour of Karen Spärck Jones. (2005)
- Megyesi, Beáta: Shallow parsing with PoS taggers and linguistic features. (2002)
- Kempe, André: Part-of-speech tagging with two sequential transducers (2001)
- Màrquez, Lluís; Padró, Lluís; Rodríguez, Horacio: A machine learning approach to POS tagging (2000)
- Daelemans, Walter; van den Bosch, Antal; Zavrel, Jakub: Forgetting exceptions is harmful in language learning (1999)