Detecting Errors in Part-of-Speech Annotation

We propose a new method for detecting errors in “gold-standard” part-ofspeech annotation. The approach locates errors with high precision based on n-grams occurring in the corpus with multiple taggings. Two further techniques, closed-class analysis and finitestate tagging guide patterns, are discussed. The success of the three approaches is illustrated for the Wall Street Journal corpus as part of the Penn Treebank.

• Type: Conference
• Year: 2003
• Where: EACL
• Authors: Markus Dickinson, Detmar Meurers
• Keywords: Approach Locates Errors, EACL 2003, Natural Language Processing, Street Journal Corpus, finitestate Tagging Guide