---
title: "Word Segmentation for Akkadian Cuneiform — Homburg 2016"
description: "They compare three families of methods: rule-based (bigram, prefix/suffix, Tango), dictionary-based… 28 references."
authors: ["Timo Homburg", "Christian Chiarcos"]
year: 2016
venue: "Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)"
source: "https://aclanthology.org/L16-1642/"
doi: "10.63317/2cqjtjuzjfzy"
licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)"
licence_url: "https://creativecommons.org/licenses/by-nc/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/homburg-2016-word-segmentation-akkadian-cuneiform/"
---
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# Word Segmentation for Akkadian Cuneiform

**Authors:** Timo Homburg; [Christian Chiarcos](https://md.research.elamur.ai/free/en/authors/christian-chiarcos/) · **Year:** 2016 · **Venue:** LREC 2016, Proceedings of the Tenth International Conference on Language Resources and Evaluation **Link:** [aclanthology.org/L16-1642](https://aclanthology.org/L16-1642/) · library `lingbulk-2016-homburg-word-segmentation-akkadian-cuneiform` · **Licence:** [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) (ELRA, LREC proceedings) — summary only

[**4** citations](https://openalex.org/works?filter=cites:W2579043414) OpenAlex, 2026-10-14 · [Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)](https://aclanthology.org/volumes/L16-1/) · [licence](https://creativecommons.org/licenses/by-nc/4.0/)

- [Publisher's page](https://aclanthology.org/L16-1642/)
- [PDF](https://aclanthology.org/L16-1642.pdf)
- [DOI 10.63317/2cqjtjuzjfzy](https://doi.org/10.63317/2cqjtjuzjfzy)
- [OpenAlex](https://openalex.org/W2579043414)

**Authors (2)**

1. [Timo Homburg](https://openalex.org/A5056967062) [ORCID](https://orcid.org/0000-0002-9499-5840) · [Semantic Scholar](https://www.semanticscholar.org/author/3424209) · h 8 · 212 citations · 72 works
2. [Christian Chiarcos](https://openalex.org/A5070093758) [ORCID](https://orcid.org/0000-0002-4428-029X) · [Semantic Scholar](https://www.semanticscholar.org/author/1723161) · h 22 · 1,646 citations · 326 works

Citations and author metrics: OpenAlex, 2026-10-14; authors with the same name are not always told apart.

## What it is about

The authors segment Akkadian cuneiform lines into words, treating the logosyllabic script as close to Chinese and Japanese. They compare three families of methods: rule-based (bigram, prefix/suffix, Tango), dictionary-based (MaxMatch and variants, minimum word count, maximum probability) and statistical or machine-learning classifiers (C4.5, MaxEnt, Naive Bayes, kNN, SVM, CRF, HMM, plus a meta-classifier). The data are Middle Babylonian tablets split 80:20 per tablet; Old Babylonian and Neo-Assyrian serve as further stages. The average-word-length baseline reaches a boundary F of about 43 and a word F of about 21. Dictionary methods are best (MinWCMatch: boundary F about 73, word F about 60), while most learners barely beat the baseline. Only Tango among the rule methods beats it.

## For Mova

- I1. Score the `tools/hbo` segmenter with the same triad: boundary F, word F and a window-based score (WindowDiff). Split the MACULA data per verse or per book, not per line, so no neighbouring line leaks into the test part, as the authors did per tablet.
- I2. A maximum-match segmenter over the `lex` and `pre` tables as a second deterministic baseline for unpointed text. The paper's finding that dictionary matching beats learners on a small corpus argues for the tables before any learned step.
- I3. Keep an average-length style floor in every report (here: one word per fixed number of letters), so a new mode of `tools/hbo` is always compared with something trivial.

I1–I3 go into `tools/hbo`, as its evaluation and its baselines for the unpointed mode. Akkadian is not a Mova language yet, so nothing goes into `languages/`.

## Institutions

[🎓**Goethe University Frankfurt** Frankfurt am Main · Germany 11 works · 292 citations](https://md.research.elamur.ai/free/en/universities/goethe-university-frankfurt/)

Also on the byline: [University of Applied Sciences Mainz](https://ror.org/02re32a17).

Topics[Akkadian and cuneiform NLP](https://md.research.elamur.ai/free/en/topics/akkadian-cuneiform-nlp/) · [Semitic languages](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Tokenization & segmentation](https://md.research.elamur.ai/free/en/topics/tokenization/)

## Cite

Cite as Timo Homburg and Christian Chiarcos. 2016. Word Segmentation for Akkadian Cuneiform. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16).

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.63317/2cqjtjuzjfzy](https://doi.org/10.63317/2cqjtjuzjfzy)

```bibtex
@inproceedings{homburg2016word,
  title = {{Word Segmentation for Akkadian Cuneiform}},
  author = {Timo Homburg and Christian Chiarcos},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
  year = {2016},
  doi = {10.63317/2cqjtjuzjfzy},
  url = {https://doi.org/10.63317/2cqjtjuzjfzy}
}
```

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