README

NUCLE Release 3.3
24 Jan 2019

This README file describes the NUS Corpus of Learner English (NUCLE).
It was collected in a collaboration project between the National
University of Singapore (NUS) Natural Language Processing (NLP) Group
led by Prof. Hwee Tou Ng and the NUS Centre for English Language
Communication (CELC) led by Prof. Siew Mei Wu. The work was carried
out as part of the PhD thesis research of Daniel Dahlmeier at the NUS
NLP Group.

The corpus is distributed under the standard NUS licensing agreement
available when downloading the corpus. Any questions regarding NUCLE
should be directed to Hwee Tou Ng at: nght@comp.nus.edu.sg

If you are using the NUCLE corpus in your work, please include a
citation of the following paper:

Daniel Dahlmeier, Hwee Tou Ng, and Siew Mei Wu (2013). Building a
Large Annotated Corpus of Learner English: The NUS Corpus of Learner
English. Proceedings of the Eighth Workshop on Innovative Use of NLP
for Building Educational Applications (BEA 2013). (pp. 22 --
31). Atlanta, Georgia, USA.


1. About
========

NUCLE is a corpus of learner English. It consists of about 1,400
essays written by university students at the National University of
Singapore on a wide range of topics, such as environmental pollution,
healthcare, etc. It contains over one million words which are
completely annotated with error categories and corrections. All
annotations have been performed by professional English instructors at
the NUS CELC.


2. Data Format 
==============

The corpus is distributed in a simple SGML format.  All annotations
come in a "stand-off" format. The start position and end position of
an annotation are given by paragraph and character offsets.
Paragraphs are enclosed in <P>...</P> tags. Paragraphs and characters
are counted starting from zero. Each annotation includes the following
fields: the error category, the correction, and optionally a
comment. If the correction replaces the original text at the given
location, it should fix the grammatical error.

Example:

<DOC nid="840">
<TEXT>
<P>
Engineering design process can be defined as a process ...
</P>
<P>
Firstly, engineering design ...
</P>
...
</TEXT>
<ANNOTATION teacher_id="173">
<MISTAKE start_par="0" start_off="0" end_par="0" end_off="26">
<TYPE>ArtOrDet</TYPE>
<CORRECTION>The engineering design process</CORRECTION>
</MISTAKE>
...
</ANNOTATION>
</DOC>
<DOC nid="862">
...


Below is a complete list of the error categories in NUCLE release 2.0:

ERROR TAG    ERROR CATEGORY
---------------------------
Vt	     Verb tense
Vm	     Verb modal
V0	     Missing verb
Vform	     Verb form
SVA	     Subject-verb-agreement
ArtOrDet     Article or Determiner
Nn	     Noun number
Npos	     Noun possesive
Pform	     Pronoun form
Pref	     Pronoun reference
Wcip	     Wrong collocation/idiom/preposition
Wa	     Acronyms
Wform	     Word form
Wtone	     Tone
Srun	     Runons, comma splice
Smod	     Dangling modifier
Spar	     Parallelism
Sfrag	     Fragment
Ssub	     Subordinate clause
WOinc	     Incorrect sentence form
WOadv	     Adverb/adjective position
Trans	     Link word/phrases
Mec	     Punctuation, capitalization, spelling, typos
Rloc	     Local redundancy
Cit	     Citation
Others	     Other errors
Um	     Unclear meaning (cannot be corrected)


3. Updates included in version 2.1
==================================

The major change made in version 2.1 is to map the error categories
Wcip and Rloc to Prep, Wci, ArtOrDet, and Rloc-.

In the original NUCLE corpus, there is not an explicit preposition
error category. Instead, preposition errors are part of the Wcip
(Wrong collocation/idiom/preposition) and Rloc (local redundancy)
error categories. In addition, redundant article or determiner errors
are part of the Rloc error category.

To facilitate the detection and correction of preposition errors and
article/determiner errors, we perform mapping of error categories in
the original NUCLE corpus. The mapping relies on POS tags, constituent
parse trees, and error annotations at the token level.

(a) Conditions to change from the error category Wcip or Rloc to Prep:

This applies to replacing a preposition by another preposition, or
deleting a preposition. The string to be replaced is one word w with
POS tag IN or TO, the parent of w is a PP in the constituent parse
tree, and the replacement is either a preposition or the empty string.

(b) Conditions to change from the error category Wcip to Prep:

This applies to inserting a preposition. The replacement is a
preposition (one word only) and the immediately following word is
tagged as VBG or is the first word of a noun phrase (NP).

(c) Conditions to change from the error category Rloc to ArtOrDet:

The single word has POS tag DT and the replacement is the empty
string.

The remaining unaffected "Wcip" errors are assigned the new error
category "Wci" and the remaining unaffected "Rloc" errors are assigned
the new error category "Rloc-".

List of 36 Prepositions:

about along among around as at beside besides between by down during
except for from in inside into of off on onto outside over through to
toward towards under underneath until up upon with within without

Below is a complete list of 28 error categories in NUCLE release 2.1:

ERROR TAG    ERROR CATEGORY
---------------------------
Vt	     Verb tense
Vm	     Verb modal
V0	     Missing verb
Vform	     Verb form
SVA	     Subject-verb-agreement
ArtOrDet     Article or Determiner
Nn	     Noun number
Npos	     Noun possesive
Pform	     Pronoun form
Pref	     Pronoun reference
Prep         Preposition
Wci	     Wrong collocation/idiom
Wa	     Acronyms
Wform	     Word form
Wtone	     Tone
Srun	     Runons, comma splice
Smod	     Dangling modifier
Spar	     Parallelism
Sfrag	     Fragment
Ssub	     Subordinate clause
WOinc	     Incorrect sentence form
WOadv	     Adverb/adjective position
Trans	     Link word/phrases
Mec	     Punctuation, capitalization, spelling, typos
Rloc-	     Local redundancy
Cit	     Citation
Others	     Other errors
Um	     Unclear meaning (cannot be corrected)


3. Updates included in version 2.2
==================================

- Fixed the bug on expanding an error annotation involving part of a
token to the full token.

- Other miscellaneous corrections were made.


4. Updates included in version 2.3
==================================

- Fixed the bug involving tokenization of punctuation symbols in the
correction string.

- Fixed the tokenization example in the README file of the M^2 scorer
to reflect the real tokenization to be used and removed irrelevant
codes from the scorer package.


5. Updates included in version 3.0
==================================

- Resolved overlapping annotations in the NUCLE corpus to make them
  non-overlapping.

- Corrected some minor mistakes in error annotations.


6. Updates included in version 3.1
==================================

- Removed duplicate annotations in the NUCLE corpus with the same span
  and correction string but different error type so as to keep only one of
  those annotations. This fix only affects 0.1% of all annotations.

- Fixed end-of-paragraph annotations so that the end offset of such
  annotations is the last character position in the paragraph. This fix
  only affects 0.7% of all annotations.

- Corrected some minor mistakes in error annotations.

- Inclusion of the CoNLL-2013 test data, with all the known problems
  described above fixed. Participating teams in the CoNLL-2014 shared
  task can make use of the CoNLL-2013 test data in training and
  developing their systems if they wish to do so.

- Fixed a minor bug in the M2 scorer that caused duplicate insertion
  edits to receive high scores.


7. Updates included in version 3.2
==================================

- Fixed the preprocessing script such that a gold edit that inserts an
  empty string is not included in the token-level gold edit and scorer
  answer files.

- Removed one edit that inserted an empty string from the CoNLL-2014
  test data. Also removed such instances from the NUCLE training data.

- Fixed a bug in the M2 scorer arising from scoring against gold edits
  from multiple annotators. Specifically, the bug sometimes caused
  incorrect scores to be reported when scoring against the gold edits
  of subsequent annotators (other than the first annotator).

- Fixed a bug in the M2 scorer that caused erroneous scores to be
  reported when dealing with insertion edits followed by deletion edits
  (or vice versa).


8. Updates included in version 3.3
==================================

- Added a subdirectory "bea2019" to contain the ERRANT typed NUCLE M2
  file for the BEA 2019 shared task on grammatical error correction.