The CoNLL-2013 Shared Task on Grammatical Error Correction

By Hwee Tou Ng, Siew Mei Wu, Ted Briscoe, Christian Hadiwinoto, Raymond Hendy Susanto, Christopher Bryant. 2013

354 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Furu Wei
2. Tao Ge
3. Mariano Felice
4. M. Zhou
5. Hwee Tou Ng
6. Dan Jurafsky
7. Xiaojun Wan
8. Mirella Lapata

In Natural Language Processing

1. Furu Wei
2. Tao Ge
3. Mariano Felice
4. M. Zhou
5. Xin Sun
6. Xiaojun Wan
7. Joel R. Tetreault
8. Dan Jurafsky

Citations in the corpus

• Instantaneous Grammatical Error Correction with Shallow Aggressive Decoding (2021, methodology): “For validation, we use CoNLL-2013 (Ng et al., 2013) that contains 1,381 sentences as our validation set.”
• A Comprehensive Survey of Grammar Error Correction (2020, background): “While the HOO-2011 [18], HOO-2012 [19], CoNLL-2013 [20] shared tasks focus on several specific error types, teams participated in the CoNLL-2014 [21] and BEA-2019 [7] shared tasks are required to correct all types of errors.”
• Parallel Iterative Edit Models for Local Sequence Transduction (2019, methodology): “The validation dataset comprises of 1381 sentence pairs from CoNLL-13 (Ng et al., 2013) test set.”
• The CoNLL-2014 Shared Task on Grammatical Error Correction (2014, background): “This task has attracted much recent research interest, with two shared tasks Helping Our Own (HOO) organized in 2011 and 2012 (Dale and Kilgarriff, 2011; Dale et al., 2012), and a CoNLL shared task on grammatical error correction organized in 2013 (Ng et al., 2013).”
• Controllable data synthesis method for grammatical error correction (2019, methodology): “We choose the test set from the CoNLL 2013 shared task (Ng et al., 2013) as our development set and report MaxMatch(M2) score (Dahlmeier and Ng, 2012) on the CoNLL-2014 shared task (Ng et al., 2014) test set.”
• The BEA-2019 Shared Task on Grammatical Error Correction (2019, background): “…Error Correction (GEC) continues the tradition of the previous Helping Our Own (HOO) and Conference on Natural Language Learning (CoNLL) shared tasks (Dale and Kilgarriff, 2011; Dale et al., 2012; Ng et al., 2013, 2014) and was motivated by the need to re-evaluate the field after a five year hiatus.”
• Overview of the NLPCC 2018 Shared Task: Grammatical Error Correction (2018, background): “And [1] extends the M 2 Scorer to deal with multiple alternative sets of gold-standard annotations, in which case there are more than one corrections that are reasonable for the current sentence.”
• The Unreasonable Effectiveness of Transformer Language Models in Grammatical Error Correction (2019, methodology): “Many of the topranked systems in the CoNLL-2013 and 2014 GEC shared tasks (Ng et al., 2013, 2014), were either based on language models or had them as integral parts of their systems (Kao et al., 2013; Yoshimoto et al., 2013; Xing et al., 2013; Lee and Lee, 2014; Junczys-Dowmunt and Grundkiewicz,…”
• Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction (2017, methodology): “We demonstrate the value of our approach, which we call the ERRor ANnotation Toolkit (ERRANT)1, by carrying out a detailed error type analysis of each system in the CoNLL-2014 shared task on grammatical error correction (Ng et al., 2014).”
• Ground Truth for Grammatical Error Correction Metrics (2015, neutral): “(Ng et al., 2013; Ng et al., 2014).”
• JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction (2017, methodology): “The CoNLL Shared Tasks used this data (Ng et al., 2014; Ng et al., 2013), and the 1,312 sentence test set from the 2014 task has become de rigueur for benchmarking GEC.”
• Artificial error generation for translation-based grammatical error correction (2016, methodology): “2, classifies errors into 28 types, after the addition of a separate category for preposition errors (Ng et al., 2013).”
• Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction (2018, methodology): “Our test sets are the CoNLL 2014 evaluation set and the JFLEG test set (Ng et al., 2014; Napoles et al., 2017).”