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# At the Crossroad of Cuneiform and NLP: Challenges for Fine-grained Part-of-speech Tagging

**Authors:** Gustav Ryberg Smidt; [Els Lefever](https://md.mova.elamur.ai/free/en/docs/papers/authors/els-lefever/); Katrien De Graef · **Year:** 2024 · **Venue:** LREC-COLING 2024 (Joint International Conference on Computational Linguistics, Language Resources and Evaluation) **Link:** [aclanthology.org/2024.lrec-main.154](https://aclanthology.org/2024.lrec-main.154/) · library `coling-2024-smidt-crossroad-cuneiform-nlp-challenges-fine` · **Licence:** [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) — summary only

[**0** citations](https://openalex.org/works?filter=cites:W7131786796) openalex-snapshot · 2026-10-14[**1** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/coling-2024-smidt-crossroad-cuneiform-nlp-challenges-fine/) of the 140673 papers whose bibliographies we read[Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)](https://aclanthology.org/volumes/2024.lrec-main/)[licence](https://creativecommons.org/licenses/by-nc/4.0/)

- [Publisher's page](https://aclanthology.org/2024.lrec-main.154/)
- [PDF](https://aclanthology.org/2024.lrec-main.154.pdf)
- [DOI 10.63317/26ihqrbhk6bq](https://doi.org/10.63317/26ihqrbhk6bq)
- [OpenAlex](https://openalex.org/W7131786796)

**Authors (3)**

1. [Gustav Ryberg Smidt](https://openalex.org/A5036463429) [ORCID](https://orcid.org/0000-0002-0107-7021) · h 2 · 12 citations · 20 works
2. [Els Lefever](https://openalex.org/A5023493215) [ORCID](https://orcid.org/0000-0002-7755-0591) · h 23 · 2382 citations · 246 works
3. [Katrien de Graef](https://openalex.org/A5040548302) [ORCID](https://orcid.org/0000-0001-6690-9098) · h 7 · 233 citations · 121 works

Citations and author metrics from openalex-snapshot (2026-10-14); authors with the same name are not always told apart.

## What it is about

The authors prepare a corpus of 121 Old Babylonian Akkadian letters from Sippar, annotated by three specialists with PoS tags, citation forms and morphemes in the ORACC style. They fine-tune FLAIR sequence taggers that use different pre-trained embeddings: multilingual, Arabic, Spanish and Japanese. The study asks three questions: whether the embeddings from a related language help, how to cut the text into sentences when no syntax is annotated, and whether the input should be transliteration or Unicode cuneiform. Verb-final sentence splitting gives 94.8% PoS accuracy in five-fold cross-validation, against 92.5% for splitting at physical lines. Feeding Unicode cuneiform instead of transliteration costs between 19.5 and 30.7 points, depending on the embedding. The paper ends by arguing that every text format carries some human reading decision.

## Ideas

- I1. Verb-final clause split as a rule: end a sentence at a finite verb and do not split at subordinating or coordinating suffixes. Test it against the book's own sentence and verse boundaries on a Hebrew prose set, for [Syntax: the clause and the sentence](https://md.mova.elamur.ai/free/en/docs/languages/hbo/08-syntax/) and the event reader.
- I2. Input representation as a measured step: run the same parser on transliteration and on script-level input, and report the loss for each. Any script-to-consonant conversion in [1. Script and pointing](https://md.mova.elamur.ai/free/en/docs/languages/hbo/01-script/) must pass this test before it is trusted.
- I3. Features without transcription: store a token's morphological features in CoNLL-U and leave out a transcription field, as the paper proposes, so that the annotation does not inherit the spelling of the transcription.

## For Mova

I1 is a rule for the clause boundaries in [Syntax: the clause and the sentence](https://md.mova.elamur.ai/free/en/docs/languages/hbo/08-syntax/), measured on `treebanks/hbo/ptnk`. I2 is a required test in [1. Script and pointing](https://md.mova.elamur.ai/free/en/docs/languages/hbo/01-script/). I3 is a design note for `treebanks/akk`, where no Akkadian treebank yet exists.

Topics: [Akkadian and cuneiform NLP](https://md.mova.elamur.ai/free/en/docs/papers/topics/akkadian-cuneiform-nlp/) · [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 10.63317/26ihqrbhk6bq](https://doi.org/10.63317/26ihqrbhk6bq)

```
@inproceedings{smidt2024at,
  title = {{At the Crossroad of Cuneiform and NLP: Challenges for Fine-grained Part-of-speech Tagging}},
  author = {Smidt, Gustav Ryberg and Lefever, Els and Graef, Katrien de},
  booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
  year = {2024},
  doi = {10.63317/26ihqrbhk6bq},
  url = {https://doi.org/10.63317/26ihqrbhk6bq}
}
```

- [← previous Camel Morph MSA: A Large-Scale Open-Source Morphological Analyzer for Modern Standard Arabic](https://md.mova.elamur.ai/free/en/docs/papers/coling-2024-khairallah-camel-morph-msa-large-scale/)
- [next → Cognate Detection for Historical Language Reconstruction of Proto-Sabean Languages: the Case of Ge'ez, Tigrinya, and Amharic](https://md.mova.elamur.ai/free/en/docs/papers/coling-2025-temesgen-cognate-detection-historical-language-reconstruction/)
- [↑ back to Semitic languages](https://md.mova.elamur.ai/free/en/docs/papers/sem/)

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