Serial Combination of Rules and Statistics: A Case Study in Czech Tagging

A hybrid system is described which combines the strength of manual rulewriting and statistical learning, obtaining results superior to both methods if applied separately. The combination of a rule-based system and a statistical one is not parallel but serial: the rule-based system performing partial disambiguation with recall close to 100% is applied first, and a trigram HMM tagger runs on its results. An experiment in Czech tagging has been performed with encouraging results. 1 Tagging of Inflective Languages Inflective languages pose a specific problem in tagging due to two phenomena: highly inflective nature (causing sparse data problem in any statistically-based system), and free word order (causing fixed-context systems, such as n-gram Hidden Markov Models (HMMs), to be even less adequate than for English). The average tagset contains about 1,000 - 2,000 distinct tags; the size of the set of possible and plausible tags can reach several thousands. Apart from agglutinative languag...

• Type: Conference
• Year: 2001
• Where: ACL
• Authors: Jan Hajic, Pavel Krbec, Pavel Kveton, Karel Oliva, Vladimir Petkevic
• Keywords: ACL 2001, ACL 2007, Inflective Languages, Rule-based System, Trigram Hmm Tagger