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*~
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.token
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FCE - Grammatical error detection
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===========================
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Detect errors in English text.
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This is a Gonito.net challenge based on data from https://ilexir.co.uk/datasets/index.html
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The aim of the challenge is to predict which tokens are incorrect.
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MultiLabel-F0.5 is used as the evaluation metric.
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Dataset reference:
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1) Compositional Sequence Labeling Models for Error Detection in Learner Writing
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Marek Rei and Helen Yannakoudakis
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In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-2016)
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2) A New Dataset and Method for Automatically Grading ESOL Texts
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Helen Yannakoudakis, Ted Briscoe and Ben Medlock
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In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL-2011)
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## Directory structure
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* `README.md` — this file
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* `config.txt` — configuration file
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* `train/` — directory with training data
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* `train/in.tsv` — Original input text for the train set
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* `train/expected.tsv` — Incorrect token indexes. Indexes start from 1.
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* `dev-0/` — directory with dev data
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* `dev-0/in.tsv` — Original input text for the dev set
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* `dev-0/expected.tsv` — Incorrect token indexes. Indexes start from 1.
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* `test-A` — directory with test data
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* `test-A/in.tsv` — Original input text for the test set
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--metric Mean/MultiLabel-F0.5:N<Mean>N<F0.5> --metric MultiLabel-F0.5:P<2>N<Total>N<F0.5> --metric MultiLabel-F0.0:P<2>N<Precision> --metric MultiLabel-F99999.0:P<2>N<Recall> --precision 4 -%
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train/in.tsv
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