In this article, the authors present a dataset of the text of the Samaritan Pentateuch with word-level linguistic annotations. The Samaritan Pentateuch is an important early witness of the Pentateuch or Torah. This dataset is based on a transcription generally taken from manuscript Dublin, Chester Beatty Library 751 (Genesis 1:1–Deuteronomy 32:36) and supplemented from manuscript Nablus (Kiryat Luza), Samaritan Synagogue, Garizim 1, where the former manuscript has not preserved the text (Deuteronomy 32:36b–34:10). The dataset is a Text-Fabric dataset. Text-Fabric is a Python package for processing annotated text corpora, which means that the dataset comes with an app, where the text can be inspected and queried using the annotations. It is also easy to perform textual and linguistic research using Python scripts and to make comparisons with other relevant textual datasets with the same annotation conventions.

In this paper, we present our approach to adding the first layers of syntactic information to an open dataset containing the text of the Samaritan Pentateuch with linguistic annotations. The Samaritan Pentateuch, written in Samaritan Hebrew, is the sacred text of the Samaritan community. The updated dataset now includes boundaries for phrase atoms and phrases. These were added using a parser previously employed to annotate Hebrew and Syriac texts morphologically. While the model predicts the locations of phrase atom and phrase boundaries, its output is not always accurate, so manual corrections were applied. This project highlights the potential of machine learning to enrich ancient texts. The syntactic features developed here can support linguistic research in the humanities and facilitate textual comparisons across ancient corpora—extending beyond morphological analysis to deepen our understanding of textual transmission. Additionally, the corrected data can be incorporated into the existing training set to improve future models.