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k-chirkunov/jeeran_semeval_2016_arabic_adaptation

Jeeran — SemEval-2016 Task 5 (Arabic) adaptation Aspect-based sentiment annotations over Jeeran reviews (Jordanian/Levantine dialectal Arabic, 29 business domains), rendered in the SemEval-2016 Task 5 subtask 1 format so that tooling written for SemEval2016_arabic runs unchanged. Contents split reviews sentences opinions train 43420 69795 182788 test 10851 17644 45520 Raw SemEval XML lives under semeval_xml/; the datasets view has one row per… See the full description on the dataset page: https://huggingface.co/datasets/k-chirkunov/jeeran_semeval_2016_arabic_adaptation.

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Jeeran — SemEval-2016 Task 5 (Arabic) adaptation

Aspect-based sentiment annotations over Jeeran reviews (Jordanian/Levantine dialectal Arabic, 29 business domains), rendered in the SemEval-2016 Task 5 subtask 1 format so that tooling written for SemEval2016_arabic runs unchanged.

Contents

splitreviewssentencesopinions
train4342069795182788
test108511764445520

Raw SemEval XML lives under semeval_xml/; the datasets view has one row per sentence with a nested opinions list.

Fields

Per opinion:

fielddescription
targetopinion target expression — verbatim substring of text
from / tocharacter offsets of target in text
categoryJeeran aspect category (flat Arabic label, 80 values)
polaritypositive / negative / neutral
span / span_from / span_tothe original human-annotated evaluative span the target was extracted from

How it differs from SemEval-2016 Arabic hotels

  • —`category` is not `ENTITY#ATTRIBUTE`. SemEval's 34 E#A labels are hotel-specific; Jeeran spans many business domains, so the original flat Arabic aspect label is kept verbatim rather than forced into an invented entity scheme.
  • —No implicit (`NULL`) targets. SemEval marks implicit aspects with target="NULL"; here opinions without an explicit target noun phrase are dropped.
  • —Sentences are opinion-bearing only. Segments carrying no annotated span are not emitted, and segments are merged where a span straddles a boundary, so no span is ever split across sentences.

Provenance and annotation quality

layersource
span, span_from/span_to, polarityhuman annotation (inline [[…]] / {…} markup in the Jeeran corpus)
categorymodel-generated (Gemma) — known to be noisy
target, from/tomodel-extracted from the human span (Gemma), accepted only when a verbatim contiguous substring of it

Target extraction outcome (286,957 candidate opinions)

statussharekept?
target extracted and verified79.56%yes
no explicit target noun phrase19.41%dropped
model would not copy verbatim1.03%dropped

Extracted targets average 1.53 words (SemEval-2016 Arabic gold: 1.20; the Jeeran spans they came from: 5.18), so the target slot is comparable in shape to SemEval rather than clause-like.

Every retained opinion is offset-verified: text[from:to] == target and the target lies inside its own span. Verified on the released files, 0 exceptions.

Two caveats for anyone using this:

  • —Dropping targetless opinions is not uniform across categories — it removes speech-act labels preferentially (نصيحة 66%, ذم 36%, مدح عام 23%, vs الموقع 5%), so the category distribution differs from the source corpus.
  • —~4.7% of targets are enumerations (brand or name lists) kept as a single target where SemEval convention would emit one opinion per item.

Licensing

The underlying reviews were collected from Jeeran; this repository does not assert a license over them. Consult the source terms before redistribution or commercial use.