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HakemBench: A Turkish Benchmark of Typed Decisions

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arXiv:2610.02293v1 Announce Type: new Abstract: HakemBench is a Turkish benchmark of typed decisions, in which the model under test reads a text, a question and a fixed set of options and returns a probability for every option. Version 1.0 is released fully open under CC BY 4.0, with 2,346 items and 4,275 choice, yes/no and score questions in seven tracks (fact-check triage, education, guardrails, legal routing, moderation, spam and phishing, and customer support). One harness scores decision quality (macro F1), calibration (from the normalised Brier score) and selective automation (from the normalised area under the generalised risk-coverage curve), combines them by a geometric mean and reports intervals from 2,000 bootstrap draws; probes for option order, paraphrase, English translation…

SourcearXiv Computational LinguisticsAuthor: Sait Furkan Teke (ufak AI)
HakemBench: A Turkish Benchmark of Typed Decisions
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[Submitted on 1 Oct 2026]

Title:HakemBench: A Turkish Benchmark of Typed Decisions

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Abstract:HakemBench is a Turkish benchmark of typed decisions, in which the model under test reads a text, a question and a fixed set of options and returns a probability for every option. Version 1.0 is released fully open under CC BY 4.0, with 2,346 items and 4,275 choice, yes/no and score questions in seven tracks (fact-check triage, education, guardrails, legal routing, moderation, spam and phishing, and customer support). One harness scores decision quality (macro F1), calibration (from the normalised Brier score) and selective automation (from the normalised area under the generalised risk-coverage curve), combines them by a geometric mean and reports intervals from 2,000 bootstrap draws; probes for option order, paraphrase, English translation and substituted names are reported alongside. Most gold labels come from blind passes of one AI model family compared with the votes of a panel of large language models from other model families; they are not human-verified. On a board of 16 rows the leader scores a composite of 0.888 and the lab's own model is 7th at 0.660. Its numbers are not blind. Earlier runs' test results shaped its training data, so its guardrail, moderation and customer support numbers are flagged; with every model scored on the other four tracks only, its composite is 0.678, 6th of 16.

Comments: 9 pages including references. Data, harness, scorer and board: this https URL, this https URL

Subjects:

Computation and Language (cs.CL)

ACM classes: I.2.7

Cite as: arXiv:2610.02293 [cs.CL]

(or arXiv:2610.02293v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2610.02293

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Sait Furkan Teke [view email] [v1] Thu, 1 Oct 2026 16:55:18 UTC (15 KB)

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  • arXiv:2610.02293v1 Announce Type: new Abstract: HakemBench is a Turkish benchmark of typed decisions, in which the model under test reads a text, a question and a fixed set of opt…

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