# Identification of Parallel Passages Across a Large Hebrew/Aramaic Corpus

arXiv: https://arxiv.org/abs/1602.08715 · HTML: https://mlsanity.com/paper/1602.08715/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Feb 2016.

## Built on by (most cited first, 6 of 6)

- [Quantitative Intertextuality from the Digital Humanities Perspective: A Survey](https://mlsanity.com/paper/2510.27045/) (2025)
- [Intertextual Parallel Detection in Biblical Hebrew: A Transformer-Based Benchmark](https://mlsanity.com/paper/2506.24117/) (2025)
- [Automatic Detection of Complex Quotation Patterns in Aggadic Literature](https://mlsanity.com/paper/2512.23504/) (2025)
- [Automatic Classification of Arabic Literature into Historical Eras](https://mlsanity.com/paper/2601.16138/) (2026)
- [MiqraBERT: Regression-Based Sentence-BERT Finetuning for Biblical Hebrew Parallel Detection](https://mlsanity.com/paper/2606.19638/) (2026)
- [Beyond Similarity: Grounded Agentic Extraction and Expert-Adjudicated Evaluation of Intertextuality in Classical Chinese Histories](https://mlsanity.com/paper/2607.27595/) (2026)

## Abstract (arXiv)

We propose a method for efficiently finding all parallel passages in a large corpus, even if the passages are not quite identical due to rephrasing and orthographic variation. The key ideas are the representation of each word in the corpus by its two most infrequent letters, finding matched pairs of strings of four or five words that differ by at most one word and then identifying clusters of such matched pairs. Using this method, over 4600 parallel pairs of passages were identified in the Babylonian Talmud, a Hebrew-Aramaic corpus of over 1.8 million words, in just over 30 seconds. Empirical comparisons on sample data indicate that the coverage obtained by our method is essentially the same as that obtained using slow exhaustive methods.