English as a Second Language
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README.txt
en_esl-ud-dev.conllu
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README.txt

# Summary

UD English-ESL / Treebank of Learner English (TLE) contains manual POS tag and dependency annotations for 5,124 English as a Second Language (ESL) sentences drawn from the Cambridge Learner Corpus First Certificate in English (FCE) dataset.

# Introduction

UD English-ESL/TLE is a collection of 5,124 English as a Second Language (ESL) sentences (97,681 words), manually annotated with POS tags and dependency trees in the Universal Dependencies formalism. Each sentence is annotated both in its original and error corrected forms. The annotations follow the standard English UD guidelines, along with a set of supplementary guidelines for ESL. The dataset represents upper-intermediate level adult English learners from 10 native language backgrounds, with over 500 sentences for each native language. The sentences were randomly drawn from the Cambridge Learner Corpus First Certificate in English (FCE) corpus. The treebank is split randomly to a training set of 4,124 sentences, development set of 500 sentences and a test set of 500 sentences. Further information is available at esltreebank.org

# Acknowledgments

The dataset and the annotation guidelines were developed at MIT by Yevgeni Berzak, Jessica Kenney, Carolyn Spadine, Jing Xian Wang, Lucia Lam, Keiko Sophie Mori, Sebastian Garza and Boris Katz.

# Obtaining the text

Due to FCE licensing restrictions, the annotations are released without
the text. To merge the annotations with the corresponding FCE sentences,
please follow these steps (require python).
1) Download the FCE dataset from https://www.ilexir.co.uk/datasets/index.html
to the current directory, thereby signing the FCE license agreement.
2) Unzip the downloaded file fce-released-dataset.zip.
3) Run "python merge.py" to obtain annotation files with the FCE sentences.

# Metadata

#ID=[document_id] [sent_id]: sentence identifier.
doc_id is the path to the FCE document from which the sentence was obtained.
sent_id is the sentence number (with respect to the automatic sentence tokenization).
#SENT=[sentence]: the error annotated xml version of the FCE sentence.
Available only in the merged version.

# Changelog

v1.4
--changed UPOS of indefinite, totality and negative pronouns from NOUN to PRON
--changed UPOS of demonstrative pronouns from DET to PRON

# Citation

You are encouraged to cite the following papers when using the TLE:

@inproceedings{berzak2016tle,
  author    = {Berzak, Yevgeni  and  Kenney, Jessica  and  Spadine, Carolyn  and  Wang, Jing Xian 
               and  Lam, Lucia  and  Mori, Keiko Sophie  and  Garza, Sebastian  and  Katz, Boris},
  title     = {Universal Dependencies for Learner English},
  booktitle = {Proceedings of the 54th Annual Meeting of the Association for Computational 
               Linguistics (Volume 1: Long Papers)},
  year      = {2016},
  publisher = {Association for Computational Linguistics},
  pages     = {737--746},
  url       = {http://www.aclweb.org/anthology/P16-1070}
}

@inproceedings{yannakoudakis2011fce,
  title={A new dataset and method for automatically grading ESOL texts},
  author={Yannakoudakis, Helen and Briscoe, Ted and Medlock, Ben},
  booktitle={Proceedings of the 49th Annual Meeting of the Association for Computational 
	     Linguistics: Human Language Technologies-Volume 1},
  pages={180--189},
  year={2011},
  organization={Association for Computational Linguistics}
}

=== Machine-readable metadata (DO NOT REMOVE!) ================================
Data available since: UD v1.3
License: CC BY-SA 4.0
Includes text: no
Genre: learner-essays
Lemmas: not available
UPOS: manual native
XPOS: manual native
Features: not available
Relations: manual native
Contributors: Berzak, Yevgeni; Kenney, Jessica; Spadine, Carolyn; Wang, Jing Xian; Lam, Lucia; Mori, Keiko Sophie; Garza, Sebastian; Katz, Boris
Contributing: elsewhere
Contact: berzak@mit.edu
===============================================================================