Sentiment Analysis and Language Models for Kwanyama

Ndapa Nakashole

doi:10.63317/4whctbu5acfp

Sentiment Analysis and Language Models for Kwanyama

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Abstract

Kwanyama is related to Swahili, Zulu, and, the more than 300 other languages in the Bantu family. Yet, unlike its better-known relatives, it remains almost entirely absent from modern Natural Language Processing (NLP). We bring Kwanyama into the LLM era of NLP through two key contributions. First, we introduce OkaSentiment, the first sentiment-labeled dataset for Kwanyama. Unlike prior African sentiment corpora that rely primarily on social media, OkaSentiment is grounded in an offline, culturally relevant domain: reviews of domestic labor relationships. The dataset is annotated by over 40 native speakers under expert supervision, with careful quality control. Second, we present OkaLM, the first language models for Kwanyama (1B, 3B, and 8B parameters), obtained by continued pretraining of LLaMA-3 checkpoints on a curated Kwanyama corpus. Together, OkaSentiment and OkaLM bring a left-behind language into the landscape of modern NLP, providing its first benchmark and language models.

Anthology ID:: 2026.lrec-1.237
Volume:: Proceedings of the Fifteenth Language Resources and Evaluation Conference
Month:: May
Year:: 2026
Address:: Palma de Mallorca, Spain
Editors:: Stelios Piperidis, Núria Bel, Henk van den Heuvel, Nancy Ide, Simon Krek, Antonio Toral
Venue:: LREC
SIG:
Publisher:: ELRA Language Resource Association
Note:
Pages:: 3031–3043
Language:
External URL:: https://lrec.elra.info/lrec2026-main-237
DOI:: 10.63317/4whctbu5acfp
Bibkey:
Cite (ACL):: Ndapa Nakashole. 2026. Sentiment Analysis and Language Models for Kwanyama. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 3031–3043, Palma de Mallorca, Spain. ELRA Language Resource Association.
Cite (Informal):: Sentiment Analysis and Language Models for Kwanyama (Nakashole, LREC 2026)
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@inproceedings{nakashole-2026-sentiment,
    title = "Sentiment Analysis and Language Models for Kwanyama",
    author = "Nakashole, Ndapa",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://aclanthology.org/2026.lrec-1.237/",
    doi = "10.63317/4whctbu5acfp",
    pages = "3031--3043",
    abstract = "Kwanyama is related to Swahili, Zulu, and, the more than 300 other languages in the Bantu family. Yet, unlike its better-known relatives, it remains almost entirely absent from modern Natural Language Processing (NLP). We bring Kwanyama into the LLM era of NLP through two key contributions. First, we introduce OkaSentiment, the first sentiment-labeled dataset for Kwanyama. Unlike prior African sentiment corpora that rely primarily on social media, OkaSentiment is grounded in an offline, culturally relevant domain: reviews of domestic labor relationships. The dataset is annotated by over 40 native speakers under expert supervision, with careful quality control. Second, we present OkaLM, the first language models for Kwanyama (1B, 3B, and 8B parameters), obtained by continued pretraining of LLaMA-3 checkpoints on a curated Kwanyama corpus. Together, OkaSentiment and OkaLM bring a left-behind language into the landscape of modern NLP, providing its first benchmark and language models."
}

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%0 Conference Proceedings
%T Sentiment Analysis and Language Models for Kwanyama
%A Nakashole, Ndapa
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F nakashole-2026-sentiment
%X Kwanyama is related to Swahili, Zulu, and, the more than 300 other languages in the Bantu family. Yet, unlike its better-known relatives, it remains almost entirely absent from modern Natural Language Processing (NLP). We bring Kwanyama into the LLM era of NLP through two key contributions. First, we introduce OkaSentiment, the first sentiment-labeled dataset for Kwanyama. Unlike prior African sentiment corpora that rely primarily on social media, OkaSentiment is grounded in an offline, culturally relevant domain: reviews of domestic labor relationships. The dataset is annotated by over 40 native speakers under expert supervision, with careful quality control. Second, we present OkaLM, the first language models for Kwanyama (1B, 3B, and 8B parameters), obtained by continued pretraining of LLaMA-3 checkpoints on a curated Kwanyama corpus. Together, OkaSentiment and OkaLM bring a left-behind language into the landscape of modern NLP, providing its first benchmark and language models.
%R 10.63317/4whctbu5acfp
%U https://aclanthology.org/2026.lrec-1.237/
%U https://doi.org/10.63317/4whctbu5acfp
%P 3031-3043

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Markdown (Informal)

[Sentiment Analysis and Language Models for Kwanyama](https://aclanthology.org/2026.lrec-1.237/) (Nakashole, LREC 2026)

Sentiment Analysis and Language Models for Kwanyama (Nakashole, LREC 2026)

ACL

Ndapa Nakashole. 2026. Sentiment Analysis and Language Models for Kwanyama. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 3031–3043, Palma de Mallorca, Spain. ELRA Language Resource Association.