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README.md

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+---
+license: cc-by-3.0
+language:
+- he
+size_categories:
+- 100K<n<1M
+---
+# HebNLI - A Natural Language Inference Dataset in Hebrew
+
+## Summary
+HebNLI is a Hebrew dataset for natural language inference (NLI) tasks.
+
+## Introduction
+This dataset is the first of its kind in the Hebrew language and aims to serve as training data for NLI tasks.
+HebNLI is based on MultiNLI, a large crowd-sourced corpus of sentences from varied genres and writing styles in the English language.
+MultiNLI was originally built by collecting hundreds of thousands of base sentences from which different taggers derived follow-up sentences that stand in one of 3 logical relations to the base sentences: entailment, contradiction or neutral.
+Different taggers were then given paired sentences - base sentence and a derived sentence. The logical relation between them was determined by the majority vote, and each pair of sentences was labled according to the determined logical relation.
+In HebNLI we used machine translation (Google Gemini) to translate the English corpus to Hebrew, such that each base sentence and its compiled derivative sentences appear in Hebrew.
+
+## Genres/Sources in HebNLI
+HebNLI comprises 7 of the original 10 genres/sources that appeared in MultiNLI:
+1. Nine eleven - Written protocols from a commitee investigating the events of 9/11.
+2. Government - Reports, speeches and press releases published on U.S.A government websites.
+3. Letters - A database of letters written in the late 90's and early 2000's.
+4. OUP (Oxford University Press) - Publications about the textile industry and about child development.
+5. Slate - Pop-culture articles published in Slate magazine.
+6. Travel - Travel guides by Berlitz press.
+7. Fiction - Texts extracted from modern works of literature.
+
+The remaining three sources were found to either be too English-oriented to be properly translated to Hebrew by machine translation ("Verbatim" magazine source), or included too many broken sentences and filler-words to be properly translated to Hebrew by machine translation (face-to-face conversations and telephone conversations sources). 
+
+## Dataset Statistics
+The table below shows the distribution of each source corpus within HebNLI (how many setences exist in the dataset from each source).
+
+| Genre/Source     |  HebNLI Corpus   |
+|------------------|------------------|
+| Nine eleven      |   1878           |
+| Government       |   76953          |
+| Letters          |   1974           |
+| OUP              |   1986           |
+| Slate            |   71082          |
+| Travel           |   75776          |
+| Fiction          |   73734          |
+
+Total # of sentences = 303,383.
+
+### HebNLI Blog Post
+XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
+
+### Original MultiNLI Paper
+https://cims.nyu.edu/~sbowman/multinli/paper.pdf
+
+## Contributors
+HebNLI was translated and checked for quality by Webiks for MAFAT, as part of the National Natural Language Processing Plan of Israel. 
+
+Contributors: Hilla Merhav Fine (Webiks), Yaniv Maylik (Webiks), Carrine Cherf (Webiks), Tal Geva (MAFAT).
+
+## Acknowledgments
+We would like to express our gratitude to Adina Williams, Nikita Nangia and Samuel R. Bowman, the creators of [the original NLI dataset MultiNLI](https://huggingface.co/datasets/nyu-mll/multi_nli).