# Researchers release 1.5-million-instance Hebrew relation extraction dataset

_Published Monday, October 19, 2026 at 2:10 AM EDT · AI, Science · Latest · Tier 2 — Notable_

Researchers released HeRE, a 1.5-million-instance dataset for training and evaluating systems that identify relationships in Hebrew text. Their preprint describes a method that filters noisy matches between knowledge bases and texts by testing whether each text supports a proposed relationship.

The researchers assessed five filtering strategies. The best open-weights model, Gemma-4-31B-it, scored F1 = 0.915 against GPT-5.4's 0.921. On a fully held-out test set annotated twice, it reached F1 = 0.844. HeRE uses automatically derived labels, a distinction from the separately annotated test set.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2610.22542)

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Canonical: https://techandbusiness.org/newswire/Sx7gnRjmhs35zX5ZcYncHN
Published: 2026-10-19T06:10:22.231Z
Story chronology: 2026-10-19T04:00:00.000Z
Retrieved: 2026-10-19T08:47:53.323Z
Publisher: Tech & Business (techandbusiness.org)