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id
int64
2
262
domain
stringclasses
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source_lang
stringclasses
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target_lang
stringclasses
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source_text
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119
target_text
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108
2
Conversational
en
nupe
Hello
We-jun
3
Conversational
en
nupe
Hi / How is it
Ke-wuyina
4
Conversational
en
nupe
Good morning
Ku be laji
5
Conversational
en
nupe
Good afternoon
Ku be egidi
6
Conversational
en
nupe
Good evening
Ku be lozu
7
Conversational
en
nupe
Good day
Ku be yina
8
Conversational
en
nupe
Good morning, how are you?
Ku be yina / ke-wona
9
Conversational
en
nupe
Nice to meet you
Ku be yeli
10
Conversational
en
nupe
Nice to meet you, too
Ku be yeli / ka mi-so
11
Conversational
en
nupe
What is your name?
Kiyi suna-wo
12
Conversational
en
nupe
My name is John
Suna me-yi John
13
Conversational
en
nupe
What are you doing?
Ki wo-jon
14
Conversational
en
nupe
I am studying
Me gba kato / Me gba takada
15
Conversational
en
nupe
I am working
Me lotun
16
Conversational
en
nupe
I am resting at home
Me fa mbo
17
Conversational
en
nupe
I am walking
Me dazan
18
Conversational
en
nupe
Where are you going?
Ba we-lo
19
Conversational
en
nupe
I am going to the market
Me lo zuko
20
Conversational
en
nupe
I am going to work
Me lo etuba
21
Conversational
en
nupe
I am going to school
Me lo makarta
22
Conversational
en
nupe
What is this?
Ki-yina
23
Conversational
en
nupe
It is a pen
Alikalemi yo
24
Conversational
en
nupe
It is a book
Takada yo
25
Conversational
en
nupe
It is a chair
Esa yo
26
Conversational
en
nupe
This is a house
Emi dana
27
Conversational
en
nupe
This is a mosque
Masalaci dana
28
Conversational
en
nupe
This is a church
Church dana
29
Conversational
en
nupe
This is a hospital
Hasibiti dana
30
Conversational
en
nupe
What happened?
Ki-jon
31
Conversational
en
nupe
Nothing
Ya-don jan
32
Conversational
en
nupe
Can you say that again?
Ga-won be
33
Conversational
en
nupe
I can't hear you
Mi-woa
34
Conversational
en
nupe
Sure, I can repeat it
Ha, mia-ganwo-be
35
Conversational
en
nupe
Yes, I will say it again
Ha, mia-ganwo-be
36
Conversational
en
nupe
Can you help me?
Wa jimi tamako wo
37
Conversational
en
nupe
I need help
Me-wa tamako
38
Conversational
en
nupe
I need your help
Me-wa gan wa-jimi tamako
39
Conversational
en
nupe
What do you need?
Ki we-wa
40
Conversational
en
nupe
Yes, I can help you
Eba, mi-jon tamako / mba, mi-jon tamako
41
Conversational
en
nupe
Who is she?
Zi wu-nyo
42
Conversational
en
nupe
Who is he?
Zi wu-nyo
43
Conversational
en
nupe
She is my wife
Yimi-me yo
44
Conversational
en
nupe
She is his wife
Yimi wun yo
45
Conversational
en
nupe
She is his mother
Nna-me yo
46
Conversational
en
nupe
She is my sister (Jnr/Snr)
Yagi-me yo / Nuguchi-me yo
47
Conversational
en
nupe
He is her husband
Eba wun yo
48
Conversational
en
nupe
He is her father
Nda wun yo
49
Conversational
en
nupe
He is her brother
Yagi-wun yo / Nuguchi-wun yo
50
Conversational
en
nupe
He is a friend
Eya me yo
51
Conversational
en
nupe
Let's go
Bi-da
52
Conversational
en
nupe
Wait, I am coming
Ka me, mai-be
53
Conversational
en
nupe
Where do you live?
Babo de-dufe
54
Conversational
en
nupe
I live in Niger State
Me de-dufe Niger State bo
55
Conversational
en
nupe
Where are you from?
Babo ye eji-wo
56
Conversational
en
nupe
I am from Delta state
Delta chi me-yo
57
Conversational
en
nupe
Who is your father?
Zeyi nda wo
58
Conversational
en
nupe
My father's name is Yusuf
Suna nda me yi Yusuf
59
Conversational
en
nupe
How are you?
Kewo-na
60
Conversational
en
nupe
I am fine thank you. What about you?
Mi-ji yebo. Wo-fa
61
Conversational
en
nupe
How's life?
Ki-wu na
62
Conversational
en
nupe
Things are going well
Wun-ge
63
Conversational
en
nupe
Things aren't going well
Wun-gia
64
Conversational
en
nupe
How are you feeling?
Kewo-na
65
Conversational
en
nupe
I am happy
Me-mani
66
Conversational
en
nupe
I am sad
Mi manian
67
Conversational
en
nupe
I am sick
Mi wo-man
68
Conversational
en
nupe
Where is she?
Babo yun-dan
69
Conversational
en
nupe
She is in the hospital
Wu dan hasibiti-o
70
Conversational
en
nupe
She is in school
Wu dan makanta
71
Conversational
en
nupe
I am waiting for you
Me-kao
72
Conversational
en
nupe
I am waiting for you at home
Me-kao mbo
73
Conversational
en
nupe
He said he would come later
Wu-gan wan-be eka degi
74
Conversational
en
nupe
He said he is hungry
Wu-gan wen gu-mada
75
Conversational
en
nupe
Are you ready?
Wa shiri jin-ani
76
Conversational
en
nupe
If you are ready we can leave now
Wa-ga shiri jin-ani, bi-da
77
Conversational
en
nupe
Give me a minute, I am almost ready
Ka-mi degi
78
Conversational
en
nupe
I am not done yet
Mi-la sajin-a
79
Conversational
en
nupe
I don't believe what I just heard
Mi ya-be eganna me yo-na
80
Conversational
en
nupe
I saw him yesterday
Mi lawo-ye stuwo
81
Conversational
en
nupe
Today
Yena
82
Conversational
en
nupe
yesterday
Stuwo
83
Conversational
en
nupe
tomorrow
Esu
84
Conversational
en
nupe
now
Gbani
85
Conversational
en
nupe
This week
Mako na
86
Conversational
en
nupe
Last week
Mako na-gwa ga-na
87
Conversational
en
nupe
Last year
Eya na-gwa ga-na
88
Conversational
en
nupe
This year
Eya-na
89
Conversational
en
nupe
Last month
Etswa na-gwa ga-na
90
Conversational
en
nupe
This month
Etswa na-gwa ga-na
91
Conversational
en
nupe
Yes
He / Ashigan
92
Conversational
en
nupe
No
Ha-ha / Unji-ashi-an
93
Conversational
en
nupe
Sorry
O-kun
94
Conversational
en
nupe
Okay / Fine
Wan-ge
95
Conversational
en
nupe
Hi
Ke-wuyina
96
Conversational
en
nupe
Hello
We-jun
97
Conversational
en
nupe
Bye
Say eka-degi
98
Conversational
en
nupe
See you soon
Say eka-degi
99
Conversational
en
nupe
I will call you later
Ma yau eka-degi
100
Conversational
en
nupe
I need to sleep
Me-wan-lele
101
Conversational
en
nupe
Good night
Say-lajin
End of preview. Expand in Data Studio

NupePilot Dataset Banner

NupePilot: A Multi-Domain English–Nupe Parallel Dataset

Dataset Description

Overview

NupePilot is a pilot parallel dataset for Nupe, a low-resource Niger-Congo language (Volta-Niger subfamily) spoken primarily in North-Central Nigeria.

Despite millions of speakers, Nupe remains significantly underrepresented in natural language processing (NLP), with only a small number of scattered datasets and limited structured resources available.

NupePilot provides a manually curated, multi-domain English–Nupe parallel corpus designed to support low-resource NLP research and applications.


Supported Tasks

  • Machine Translation (English → Nupe)
  • Text-to-Text Generation
  • Conversational AI
  • Cross-lingual transfer learning

Languages

  • English (en)
  • Nupe (nup)

Dataset Structure

Data Instances

Each example consists of:

{
  "id": 1,
  "domain": "conversation",
  "source_lang": "en",
  "target_lang": "nupe",
  "source_text": "What are you doing?",
  "target_text": "Ki wo-jon?"
}

Data Fields

  • id: Unique identifier
  • domain: Domain category (conversation, health, news)
  • source_lang: Source language (English)
  • target_lang: Target language (Nupe)
  • source_text: Original sentence
  • target_text: Translated sentence

Dataset Size

  • Total examples: ~200+

Current Version Scope

This version of the dataset primarily contains everyday conversational phrases, with a smaller number of examples from additional domains such as:

  • Health and public information
  • News

Future versions of NupePilot will expand coverage to include more diverse domains, enabling broader applicability for NLP tasks.

Data Source

Sentences were curated from:

  • Public-domain text sources
  • Benchmark-style datasets (e.g., conversational and news corpora)
  • Manually constructed examples
  • Contemporary informational content

Personal and Sensitive Information

This dataset does not contain any personal or sensitive data.

Motivation

While recent years have seen progress in African NLP, many languages remain underrepresented. Nupe is one such example, with minimal digital presence and very few standardised datasets for machine learning.

This dataset is motivated by the need to:

  • Enable machine translation for Nupe
  • Support inclusive and equitable AI development
  • Provide foundational data for future research
  • Encourage community-driven language resource creation

Potential Impact

The rapid growth of AI technologies has enabled applications such as:

  • Localised educational tools
  • Language translation systems
  • Conversational agents
  • Healthcare information access

By open-sourcing this dataset, we aim to ensure that Nupe-speaking communities are not excluded from these advancements.

This dataset can serve as a foundation for building:

  • Translation systems
  • Chatbots/Conversational AI systems
  • Language learning tools, and
  • Public health communication systems for Nupe speakers

Considerations for Using the Data

Intended Use

This dataset is intended for:

  • Academic research
  • Low-resource NLP experimentation
  • Prototyping translation systems
  • Educational and linguistic analysis

Limitations

  • Small dataset size (pilot-scale)
  • Limited domain coverage

Biases

  • Domain imbalance (limited domains, and currently highly skewed to everyday conservational sentences)
  • Translation variability

Risks

  • Not suitable for production-level systems
  • May not generalise beyond included domains

Additional Information

Dataset Curators

License

This dataset is released under the CC BY 4.0 License.

Credits

Created using Adaptive Data by Adaption.

Citation

If you use this dataset, please cite:

@dataset{nupepilot2026,
  title={NupePilot: A Multi-Domain English–Nupe Parallel Dataset},
  authors={amina mardiyyah rufai, fatima tasallah rufai},
  year={2026},
  url={https://huggingface.co/datasets/NupePilot/nupepilot}
}
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