Lost in Collocation: When Arabic Collocation Dictionaries Lack Collocations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Arabic has always been in bad need of collocation dictionaries. However, the only two recent English/Arabic & Arabic/English dictionaries that emerged, Dar El-Ilm’s Dictionary of Collocations (DEDC) and Al-Hafiz Arabic Collocations Dictionary (AACD) suffer from serious problems. Although DEDC has a wide range of items covered, it suffers from the serious problem of disregarding the Arabic legacy of collocational equivalents while translating the English terms. English collocation structures, therefore, are translated into free Arabic word combinations. AACD, on the other hand, has the perceived problem of the deficiency in the range of items covered for each entry, ignoring that Arabic, a lexically rich language, can provide a remarkable range of collocational material on different word entries. The two dictionaries would be of greater help for language learners and translation practitioners if those problems were addressed. This paper focuses on those particular weaknesses putting forward alternative suggestions about how to tackle the deficiencies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it