Title | A Comparison of Rule-Based and Machine Learning Methods for Identifying Non-nominal It |
Publication Type | Book Chapter |
Year of Publication | 2000 |
Authors | Evans R |
Editor | Christodoulakis DN |
Book Title | Natural Language Processing — NLP 2000 |
Series Title | Lecture Notes in Computer Science |
Volume | 1835 |
Pagination | 233-240 |
Publisher | Springer |
City | Berlin / Heidelberg |
ISBN Number | 978-3-540-67605-8 |
Abstract | The pronoun it is noted to be used in a variety of non-nominal ways. The identification of non-nominal pronouns is important in information retrieval, machine translation and automatic summarisation. Given that previous work has only tackled a subset of those non-nominal uses, a machine learning method for identification of all instances of non-nominal it is presented. The machine learning method is compared with a rule-based approach. The performance of each implementation is evaluated. The construction of an annotated corpus and training data are also described. |
DOI | 10.1007/3-540-45154-4_22 |
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