Correcting Comma Errors in Learner Essays, and Restoring Commas in Newswire Text

2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 284–294, Montr´eal, Canada, June 3-8, 2012. c⃝2012 Association for Computational Linguistics Correcting Comma Errors in Learner Essays, and Restoring Commas in Newswire Text Ross Israel Indiana University Memorial Hall 322 Bloomington, IN 47405, USA raisrael@indiana.edu Joel Tetreault Educational Testing Service 660 Rosedale Road Princeton, NJ 08541, USA jtetreault@ets.org Martin Chodorow Hunter College of CUNY 695 Park Avenue New York, NY 10065, USA mchodoro@hunter.cuny.edu Abstract While the field of grammatical error detection has progressed over the past few years, one area of particular difficulty for both native and non-native learners of English, comma place- ment, has been largely ignored. We present a system for comma error correction in English that achieves an average of 89% precision and 25% recall on two corpora of unedited student essays. This system also achieves state-of-the- art performance in the sister task of restor- ing commas in well-formed text. For both tasks, we show that the use of novel features which encode long-distance information im- proves upon the more lexically-driven features used in prior work. 1 Introduction Automatically detecting and correcting grammati- cal errors in learner language is a growing sub-field of Natural Language Processing. As the field has progressed, we have seen research focusing on a range of grammatical phenomena including English articles and prepositions (c.f. Tetreault et al., 2010; De Felice and Pulman, 2008), particles in Korean and Japanese (c.f. Dickinson et al., 2011; Oyama, 2010), and broad approaches that aim to find mul- tiple error types (c.f Rozovskaya et al., 2011; Ga- mon, 2011). However, to the best of our knowledge, there has not been any research published specifi- cally on correcting erroneous comma usage in En- glish (though there have been efforts such as the MS Word grammar checker, and products like Gram- marly and White Smoke that include comma check- ing). There are a variety of reasons that motivate our interest in attempting to correct comma errors. First of all, a review of error typologies in Leacock et al. (2010) reveals that comma usage errors are the fourth most common error type among non-native writers in the Cambridge Learner Corpus (Nicholls, 1999), which is composed of millions of words of text from essays written by learners of English. The problem of comma usage is not limited to non- native writers; six of the top twenty error types for native writers involve misuse of commas (Connors and Lunsford, 1988). Given these apparent deficits among both non-native and native speakers, devel- oping a sound methodology for automatically iden- tifying comma errors will prove useful in both learn- ing and automatic assessment environments. A quick examination of English learner essays re- veals a variety of errors, with writers both overusing and underusing commas in certain contexts. Con- sider examples (1) and (2): (1) erroneous: If you want to be a master you should know your subject well. corrected: If you want to be a master , you …

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