[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/aclbulk-2018-giovannetti-constructing-annotated-resource-part-speech/) [home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [Ancient Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/hbo/) / Constructing an Annotated Resource for Part-Of-Speech Tagging of Mishnaic Hebrew # Constructing an Annotated Resource for Part-Of-Speech Tagging of Mishnaic Hebrew **Authors:** [Emiliano Giovannetti](https://md.mova.elamur.ai/free/en/docs/papers/authors/emiliano-giovannetti/); [Davide Albanesi](https://md.mova.elamur.ai/free/en/docs/papers/authors/davide-albanesi/); [Andrea Bellandi](https://md.mova.elamur.ai/free/en/docs/papers/authors/andrea-bellandi/); Simone Marchi; Alessandra Pecchioli · **Year:** 2018 · **Venue:** Proceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018) **Link:** [aclanthology.org/2018.clicit-1.39](https://aclanthology.org/2018.clicit-1.39/) · library `aclbulk-2018-giovannetti-constructing-annotated-resource-part-speech` · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) [**0** citations](https://openalex.org/works?filter=cites:W2907516253) openalex · 2026-10-19[**1** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2018-giovannetti-constructing-annotated-resource-part-speech/) of the 140673 papers whose bibliographies we read[Proceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018)](https://aclanthology.org/volumes/2018.clicit-1/)[licence](https://creativecommons.org/licenses/by/4.0/) - [Publisher's page](https://aclanthology.org/2018.clicit-1.39/) - [PDF](https://aclanthology.org/2018.clicit-1.39.pdf) - [DOI 10.4000/books.aaccademia.3394](https://doi.org/10.4000/books.aaccademia.3394) - [OpenAlex](https://openalex.org/W2907516253) **Authors (5)** 1. [Emiliano Giovannetti](https://openalex.org/A5052924491) [ORCID](https://orcid.org/0000-0002-0716-1160) · [Semantic Scholar](https://www.semanticscholar.org/author/3298275) · h 6 · 130 citations · 56 works 2. [Davide Albanesi](https://openalex.org/A5045500478) [ORCID](https://orcid.org/0000-0002-2645-2238) · [Semantic Scholar](https://www.semanticscholar.org/author/38879650) · h 2 · 17 citations · 12 works 3. [Andrea Bellandi](https://openalex.org/A5023816166) [ORCID](https://orcid.org/0000-0002-1900-5616) · [Semantic Scholar](https://www.semanticscholar.org/author/1871708) · h 7 · 166 citations · 72 works 4. [Simone Marchi](https://openalex.org/A5033262719) [ORCID](https://orcid.org/0000-0003-4320-6466) · [Semantic Scholar](https://www.semanticscholar.org/author/145992240) · h 7 · 206 citations · 30 works 5. Alessandra Pecchioli [Semantic Scholar](https://www.semanticscholar.org/author/47210691) Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart. ## What it is about The Babylonian Talmud Translation Project had no tagged Mishnaic Hebrew to train a stochastic POS tagger, so the team hand-tagged about 10,400 tokens of the Mishna inside their translation database. The annotation tool reuses earlier subtoken splits (stems, prefixes, suffixes) and proposes the most frequent past analysis. The tagset is their own, with about twenty labels, because the UD Hebrew tagset is too coarse and has no prefix tags. Each word gets two layers: a "category" (out of context) and a "function" (in context); only the function layer is used for training. Three off-the-shelf taggers (Stanford, HunPos, TreeTagger) were scored with 10-fold cross-validation: Stanford 87.9%, TreeTagger 86.7%, HunPos 86.3%. Lemmatisation and the Babylonian Aramaic of the Gemara are the stated next steps. ## Ideas - I1. Keep two parallel layers in the Mishnaic lexicon: a context-free category and an in-context function for each form. The parser then decides the function, and the lexicon still shows that a form such as a verb-or-adjective reading exists. - I2. Give prefixes their own tags (preposition, conjunction, article, relative) inside `tools/hbo` segment output, and fold them into UD only at the last step. The paper's reason is exactly that UD has no prefix tags. - I3. Use the 10-fold cross-validation with the 87.9% figure as the bar for a Mishnaic test of `tools/hbo`, and first compare a deterministic lexicon-plus-rules tagger with it, before any learned model is added. ## For Mova I1 goes into [The lexicon](https://md.mova.elamur.ai/free/en/docs/languages/hbo/10-lexicon/); I2 goes into [Pronouns, particles and prepositions](https://md.mova.elamur.ai/free/en/docs/languages/hbo/05-pronouns-particles/) (prefix inventory) and [13. Biblical Hebrew in Mova: the tools](https://md.mova.elamur.ai/free/en/docs/languages/hbo/13-mova-tools/) (the segmenter output); I3 is a measure for [11. Mishnaic Hebrew (hbo-x-mishnaic)](https://md.mova.elamur.ai/free/en/docs/languages/hbo/11-mishnaic/) and `tools/hbo`. Topics: [Part-of-speech tagging](https://md.mova.elamur.ai/free/en/docs/papers/topics/part-of-speech-tagging/) ## Cite The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.4000/books.aaccademia.3394](https://doi.org/10.4000/books.aaccademia.3394) ``` @inproceedings{giovannetti2018constructing, title = {{Constructing an Annotated Resource for Part-Of-Speech Tagging of Mishnaic Hebrew}}, author = {Giovannetti, Emiliano and Albanesi, Davide and Bellandi, Andrea and Marchi, Simone and Pecchioli, Alessandra}, booktitle = {Proceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018)}, year = {2018}, doi = {10.4000/books.aaccademia.3394}, url = {https://doi.org/10.4000/books.aaccademia.3394} } ``` - [← previous Stylometry in Computer-Assisted Translation: Experiments on the Babylonian Talmud](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2017-giovannetti-stylometry-computer-assisted-translation-experiments/) - [next → A Characterwise Windowed Approach to Hebrew Morphological Segmentation](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2018-zeldes-characterwise-windowed-approach-hebrew-morphological/) - [↑ back to Ancient Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/hbo/) ## References 18 references, 3 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. 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