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The Arabic Error Type Annotation tool aims to annotate Arabic error types following the ALC tagset annotation.

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Arabic Error Type Annotation

Description

The Arabic Error Type Annotation tool (ARETA) aims to annotate Arabic error types following the Arabic Learner Corpus (ALC) tagset annotation. ARETA is described in Automatic Error Type Annotation for Arabic (Belkebir and Habash, 2021).

Installation

You will need Python 3.7 and above (64-bit).

  1. Install CamelTools.
  2. Install requirements.
pip install -r requirements.txt

Usage

Error Type Annotation:

Usage: annotate_err_type_ar.py [OPTIONS] --sys_path system --ref_path reference 
where
    system - the system output
    reference - the reference file
OPTIONS
    --show_edit_paths - whether to show the shortest edit paths or not; defaults to false.
    --output_path - output file directory; defaults to standard output.
    

Example:

python annotate_err_type_ar.py --sys_path sample/sys_sample.txt --ref_path sample/ref_sample.txt

The output lists triplets of system, reference and error types. For the complete list of error types, see table of error types below.

Example:

System sentence: إن أمتحان الاستاذة صعبة

Reference sentence: إن إمتحان الأستاذ صعب

Annotation result:

System Reference Error type
إن إن UC
أمتحان إمتحان OH
الاستاذة الأستاذ OH+XG
صعبة صعب XG

Note: It is important to note that every sentence in the system/reference outputs must start with an s. Refer to sample/sys_sample.txt and sample/ref_sample.txt for examples on how these files should look like.

Annotation and evaluation using m2 files (Command Line):

Usage: annotate_eval_ar.py [OPTIONS] system source_reference 
where
    system - the system output
    source_reference - source sentences with gold token edits (.m2 file)
OPTIONS

Example:

python annotate_eval_ar.py sample/CLMB-1 sample/QALB-Test2014.m2

This generates:

  1. annot_input_ref.tsv file in the output folder that contains the error types annotation between the input and the reference.
  2. annot_input_sys.tsv file in the output folder that contains the error types annotation between the input and the system.
  3. subclasses_results_CLMB-1.tsv file in the results folder. This file contains the results of the evaluation of the system's output against the reference.

Utilities

Generate source from m2 file

Usage: utilities/generate-m2-source.py m2-file
where
    m2-file -   the m2 file

Example:

python utilities/generate-m2-source.py sample/QALB-Test2014.m2 > sample/QALB-Test2014.source.sent

Generate reference from m2 file

Usage: utilities/generate-m2-reference.py m2-file
where
    m2-file -   the m2 file

Example:

python utilities/generate-m2-reference.py sample/QALB-Test2014.m2 > sample/QALB-Test2014.reference.cor

Adjust the alignment

This re_alignment tool realigns files from Ossama's basic aligner by shifting the word in null -> word pair to the word before or after according to minimum edit distance.

Usage: utilities/adjust_align_tool.py file_to_adjust_align
where
    file_to_adjust_align -   File to be realigned (should follow Ossama's basic alignement file format)

Example:

python utilities/adjust_align_tool.py sample/align.basic > sample/align.adjust

Configuration

In the configuration file config.json, the user should specify the mode of the morphological analyser. The default value is analyser in which all the analyses are considered. The second option is mle and in this case, we need to specify the parameter mle_top which represents the maximum number of analyses to be considered. The uc parameter takes the values 0 or 1. 0 to indicate that we do not consider the unchanged error types, 1 otherwise.

{
  "mode": "analyser",
  "mle_top": ""
}

Table of Error Types

Class Sub-class Description Arabic Example Buckwalter Transliteration
Orthographic OH Hamza error اكثر← أكثر Akvr → >kvr
OT Confusion in Ha and Ta Mutadarrifatin مشاركه ← مشاركة m$Arkh → m$Arkp
OA Confusuion in Alif and Ya Mutadarrifatin علي ← على Ely → ElY
OW Confusion in Alif Fariqa وكانو ← وكانوا wkAnw→ wkAnwA
ON Confusion Between Nun and Tanwin ثوبن ← ثوبٌ vwbn → vwbN
OS Shortening the long vowels أوقت ← أوقات >wqt → >wqAt
OG Lengthening the short vowels نقيمو ← نقيم nqymw → nqym
OC Wrong order of word characters تبرينا ← تربينا tbrynA → trbynA
OR Replacement in word character(s) مصلنا ← وصلنا mSlnA → wSlnA
OD Additional character(s) يعدوم ← يدوم yEdwm → ydwm
OM Missing character(s) سالين ← سائلين sAlyn → sA}lyn
OO Other orthographic errors - -
Morphological MI Word inflection معروف ← عارف mErwf → EArf
MT Verb tense تفرحني ← أفرحتني tfrHny → >frHtny
MO Other morphological errors - -
Syntax XC Case رائع ← رائعاً rA}E → rA}EAF
XF Definiteness السن ← سن Alsn → sn
XG Gender الغربي ← الغربية Algrby → Algrbyp
XN Number فكرتي ← أفكاري fkrty → >fkAry
XT Unnecessary word على ←Null ElY →Null
XM Missing word Null ← على Null → ElY
XO Other syntactic errors - -
Semantic SW Word selection error من ← عن mn → En
SF Fasl wa wasl (confusion in conjunction use/non-use) سبحان ← فسبحان sbHAn → fsbHAn
SO Other semantic errors - -
Punctuation PC Punctuation confusion المتوسط. ← المتوسط، AlmtwsT. → AlmtwsT،
PT Unnecessary punctuation العام, ← العام AlEAm, → AlEAm
PM Missing punctuation العظيم ← العظيم، AlEZym → AlEZym،
PO Other errors in punctuation - -
Merge MG Words are merged ذهبتالبارحة ← ذهبت البارحة *hbtAlbArHp → *hbt AlbArHp
Split SP Words are split المحا دثات ← المحادثات AlmHA dvAt → AlmHAdvAt

Citation

If you find ARETA useful in your research, please cite Automatic Error Type Annotation for Arabic (Belkebir and Habash, 2021) (PDF) (BIB).

License

This tool is available under the MIT license. See the LICENSE file for more info.

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