Dataset Viewer
Auto-converted to Parquet Duplicate
tgt_text
stringlengths
1
568
src_text
stringlengths
1
487
src_lang
stringclasses
1 value
tgt_lang
stringclasses
7 values
eng
tig
tig_Ethi
eng_Latn
Correct the mistakes, if there are any.
ለቀለጥ አስንዩ፡ ሀለ ምን ገብእ።
tig_Ethi
eng_Latn
Yanni ruined his reputation.
ያኒ ስምዐቱ ኣከ።
tig_Ethi
eng_Latn
Stop doing that.
እሊ ትረስዑ።
tig_Ethi
eng_Latn
Put the light on. I can't see a thing.
ለኑር ወልዕ። ሐቴ እግል እርኤ እቀድር ይህሌኮ።
tig_Ethi
eng_Latn
Tom will be tough to replace.
ቶም እግል ቶኮኦት ክቡድ እግል ልግበእ ቱ።
tig_Ethi
eng_Latn
I don't feel much like eating.
አነ ስፍሩይ ይህለኮኒ::
tig_Ethi
eng_Latn
Bruno will be hanged.
ብሩኖ እግል ልሸነቅ ቱ።
tig_Ethi
eng_Latn
It's a quarter past nine.
ሳዐት 9:15 ህለት::
tig_Ethi
eng_Latn
I'll wait for you in the car.
እተ መኪነት እግል እጸበርኪ ቱ።
tig_Ethi
eng_Latn
That's awesome!
ቀሊል
tig_Ethi
eng_Latn
Give me your knife.
ሰኪንከ ነይከ ሀብኒ.
tig_Ethi
eng_Latn
I will remain at home.
እት ቤት እግል እጽነሕ ቱ።
tig_Ethi
eng_Latn
Do rabbits eat acorns?
መናትሌ ፍሬ ናይ ዕጨይ ኦኣክ በልዐ?
tig_Ethi
eng_Latn
It is all Greek to me.
አነ ኢይኣምርኮኒ?
tig_Ethi
eng_Latn
She's angry.
ህታ ሓርቀት
tig_Ethi
eng_Latn
How did you get to know him?
ከፎ ተኣመርከ ምስለ።
tig_Ethi
eng_Latn
Ziri tried again.
ዚሪ ካልእ ዶል ጀረበ።
tig_Ethi
eng_Latn
Right?
ለ አማን ?
tig_Ethi
eng_Latn
That's mine.
ነዬ’ተ እለ።
tig_Ethi
eng_Latn
Is that a new car?
እለ መኪነት ሐዳስ ተ?
tig_Ethi
eng_Latn
He writes very quickly.
ህቱ መረ እብ ሸፋግ ከትብ.
tig_Ethi
eng_Latn
She left.
ህተ እዜ ጌሰት::
tig_Ethi
eng_Latn
Who phoned them?
ምን ትላከየ፧ ህተ ምን ዘብጣ ዲባ፧
tig_Ethi
eng_Latn
I worked all day yesterday.
አነ ማሌ አምዕል ኩለ ሸቄኮሀ::
tig_Ethi
eng_Latn
Prices are going down.
ለአስዓር ትትከሬ ህሌት።
tig_Ethi
eng_Latn
She bought vegetables yesterday.
ህተ ማሌ ሐመሊት ተዛቤት.
tig_Ethi
eng_Latn
Hi.
አስናይ ደሐን መጽአኩም!
tig_Ethi
eng_Latn
Hundreds of buffaloes moved toward the lake.
አምኣት ምን ዐገበታት ሸነክለ መራት ትሐረከው።
tig_Ethi
eng_Latn
I hope that it rains tomorrow.
ፈጅር ትዝለም እተምኔ።
tig_Ethi
eng_Latn
What's going on?
ሚ ጀሬ ሀለ እንሰር?
tig_Ethi
eng_Latn
She is very fond of flowers.
ህተ ዕንቦባታት ትፈቴ::
tig_Ethi
eng_Latn
Kudos!
ፍቱይ
tig_Ethi
eng_Latn
I study.
አነ አነብብ ህለኮ::
tig_Ethi
eng_Latn
Don't talk.
ሐቴ ኢይቲበልኒ::
tig_Ethi
eng_Latn
We'll need it.
እግል ንሕዘየ ቱ።
tig_Ethi
eng_Latn
Yanni had a flower for Skura.
ያኒ እግል ስኮረ ፍዮሪ ሀበየ።
tig_Ethi
eng_Latn
Did you phone him?
አተሰልክን ዲቡ?
tig_Ethi
eng_Latn
We're going north.
ሕነ ሸነክ ቅብለት ውጅሃም ህሌነ።
tig_Ethi
eng_Latn
Come inside.
ተስጂል ኢተት።
tig_Ethi
eng_Latn
Tom has been drinking a lot.
ቶም ብዙሕ ሰቴ።
tig_Ethi
eng_Latn
I'm too tired.
አነ መራ ሰአንኮ
tig_Ethi
eng_Latn
What happened to your nose?
ኣንፍከ ሚ ገብአ?
tig_Ethi
eng_Latn
I can give you very little money.
ሽውየ ግሩሻት እግል ሀበከ እገድር ።
tig_Ethi
eng_Latn
Ziri smokes hash.
ዚሪ ስጃረት ሐሺሽ ሰቴ።
tig_Ethi
eng_Latn
Could you please say that again?
እሊ ደገምካሁ?
tig_Ethi
eng_Latn
Are you younger than him?
እንተ ምኖም ትንእሽ?
tig_Ethi
eng_Latn
That does not make sense.
ሌሀይ ግማመት ቱ።
tig_Ethi
eng_Latn
That isn't for me to say.
እለ አነ ብህለ ኢአነ::
tig_Ethi
eng_Latn
Get up!
ፍዘዕ! ቅነጽ! ሐሶሴ!
tig_Ethi
eng_Latn
I love her.
እፈቴኪ።
tig_Ethi
eng_Latn
Read this.
ቅረእ፤ ዕረድ፤ ቄቄ።
tig_Ethi
eng_Latn
Have a nice day.
ላሊ በኪተት። ላሊ ኬር።
tig_Ethi
eng_Latn
Where was he going?
ህቱ አየ ጌሰ?
tig_Ethi
eng_Latn
Are you out of your minds?
ወሽወሽከ?
tig_Ethi
eng_Latn
Go ahead!
ነዐ
tig_Ethi
eng_Latn
I was happy to see him.
እግል ርእየትከ ፈርሐኮ።
tig_Ethi
eng_Latn
Start.
አስተብዴ!
tig_Ethi
eng_Latn
Yanni tends to be pessimistic.
ያኒ ሰአዮብ'መ በትክ::
tig_Ethi
eng_Latn
Have a safe trip.
ገበይ ሰላም።
tig_Ethi
eng_Latn
He walks.
ህተ ገይስ ሀሌት.
tig_Ethi
eng_Latn
He's afraid of his own shadow.
ህቱ ምን ጽላሉ ፈፍህ።
tig_Ethi
eng_Latn
You look sharp.
ሻጥር ትመስል።
tig_Ethi
eng_Latn
What he says is true.
ኣማናቱ
tig_Ethi
eng_Latn
How old is Mom?
ዕምር እምዬ ከም ቱ?
tig_Ethi
eng_Latn
What?
ሚ ሐዲስ ሀለ?
tig_Ethi
eng_Latn
He's not jealous.
ህቱ ቄንኣይ ኢኮን።
tig_Ethi
eng_Latn
It doesn't matter.
ኢለሀመኒ።
tig_Ethi
eng_Latn
He approved.
አይወ ቤለ።
tig_Ethi
eng_Latn
The new professor is in the classroom.
ለመምህር ለሐዲስ እት ፈስል ሀለ።
tig_Ethi
eng_Latn
The eagle's home is the peak.
ጋባት ቤቶም እት አካን ውቅል በኑ።
tig_Ethi
eng_Latn
With whom were you speaking?
እንተ ምስል ምን ትትሀጌ ህሌከ?
tig_Ethi
eng_Latn
He's hanged himself.
ህተ ትሸነቀት::
tig_Ethi
eng_Latn
Wow!
ዬእ!
tig_Ethi
eng_Latn
Did something happen?
ሚ ጀሬ ሀለ?
tig_Ethi
eng_Latn
Yanni never changed.
ያኒ ኢትቀየረ።
tig_Ethi
eng_Latn
Fantastic.
መልሃይከ!
tig_Ethi
eng_Latn
What do people call you?
ምን ታ ስምካ?
tig_Ethi
eng_Latn
I can count to a hundred.
አነ እስከ ሐቴ ምእት ሐስብ::
tig_Ethi
eng_Latn
You will have to wait and see.
ሕነ ላዝም ንታኬ ወእንረኤ::
tig_Ethi
eng_Latn
When the cat's away the mice will play.
ዶለ ዱሙ እት ቤት የዐለተ አነጺት ዲበ ጠዉለት ተልሃ.
tig_Ethi
eng_Latn
Oslo is the capital of Norway.
ኦስሎ ዓስመት ኖርወይ ተ።
tig_Ethi
eng_Latn
Am I forgetting anything?
ሓጀት ትረሰዐከ፧
tig_Ethi
eng_Latn
It's so cool!
በኪት ሐቆ ሕሙም ኦሮት ነፈር ሕሙም ህለ።
tig_Ethi
eng_Latn
You're ill-mannered.
እንተ ሸራር እንተ።
tig_Ethi
eng_Latn
Mornin', time to wake up.
ሰኒ ምዩያም. ከለስ እዜ ቅነጽ፡፡
tig_Ethi
eng_Latn
Who are they?
ምን ተ ህተ?
tig_Ethi
eng_Latn
Sami looked at the dog.
ሳሚ አስከ ከልብ ገንሐ።
tig_Ethi
eng_Latn
I have gas.
አነ ገዝ ብዬ ።
tig_Ethi
eng_Latn
I saw him in the mosque.
እተ ጃምዕ ረኤክዉ።
tig_Ethi
eng_Latn
Get lost.
እብለ ፍገር።
tig_Ethi
eng_Latn
It's on fire!
ነድድ!
tig_Ethi
eng_Latn
I have no appetite.
አነ ስፍሩይ ይህለኮ::
tig_Ethi
eng_Latn
The Netherlands is a small country.
ሆላንድ ደውለት ንኢሽ ተ።
tig_Ethi
eng_Latn
Yanni continued to drink.
ያኒ ስታይ አተላለ።
tig_Ethi
eng_Latn
Swap.
በደሎት።
tig_Ethi
eng_Latn
How's it going?
ሚቱ ለሰበብ፧
tig_Ethi
eng_Latn
It's beyond belief.
ኢልትአመን።
tig_Ethi
eng_Latn
My sister also became Muslim.
ሕቼመ አስሌማይት ገብአት።
tig_Ethi
eng_Latn
Did you go to the doctor?
እንተ ሐኪም ግስከ፧
tig_Ethi
eng_Latn
End of preview. Expand in Data Studio

Tigre Parallel Multilingual Dataset (Tigre-Data 1.0)

Overview

This repository introduces the Parallel Multilingual Text component of the Tigre language resource collection. Tigre is an under-resourced South Semitic language within the Afro-Asiatic family.

The goal of Tigre-Data 1.0 is to accelerate research in low-resource NLP and morphologically rich language modeling. This dataset provides a clean, high-quality parallel corpus essential for developing and evaluating Machine Translation (MT) systems for Tigre.

Data Source & Licensing

The parallel sentences in this dataset originate from Tatoeba.org, a community-driven multilingual corpus released under the CC-BY 2.0 license. All Tigre translations were contributed by native-speaking members of the Tigre diaspora, reflecting years of collective volunteer effort to expand the language’s digital presence. This contribution is significant, as, by the end of 2025, the Tigre language on Tatoeba.org is supported by 77 registered translators working across more than ten other languages, resulting in a larger sentence pool than 93% of the 429 hosted languages.

Included Data & Structure

Data Modalities

This repository contains the Parallel Multilingual Text modality.

Dataset Structure

The dataset is provided in Parquet format, compatible with the Hugging Face datasets library.

tigre-data-parallel-multilingual/
├── README.md
└── tigre-data-parallel-multilingual.parquet

Dataset Statistics and Metrics

The dataset contains 329,554 parallel sentences across seven target languages.

Corpus Totals

Statistic Value
Total Sentences in Corpus 329,554
Total Source Words (Tigre) 1,072,951
Total Target Words 1,240,407
Avg Sentence Length (Tigre) 3.26 words
Avg Sentence Length (Target) 3.76 words

Language Pair Distribution (Tigre → Target Language)

Target Language Total Sentences Percentage Tigre Words Avg Src Words/Sentence Target Words Avg Tgt Words/Sentence
ara_Arab (Arabic) 49,964 15.16% 172,645 3.46 160,675 3.22
deu_Latn (German) 80,120 24.31% 258,160 3.22 321,966 4.02
eng_Latn (English) 156,206 47.40% 508,318 3.25 610,321 3.91
nno_Latn (Norwegian Nynorsk) 6,001 1.82% 14,055 2.34 14,619 2.44
nob_Latn (Norwegian Bokmål) 8,222 2.49% 21,567 2.62 23,481 2.86
swe_Latn (Swedish) 28,554 8.66% 96,439 3.38 107,562 3.77
tir_Ethi (Tigrinya) 487 0.15% 1,767 3.63 1,783 3.66

How to Download & Load the Dataset

from datasets import load_dataset
import pandas as pd

dataset = load_dataset(
    "BeitTigreAI/tigre-data-parallel-multilingual",
    data_files={
        "train": "train.parquet",
        "validation": "validation.parquet"
    }
)

print("Dataset Info:")
print(dataset)

df_train = dataset["train"].to_pandas()
lang_counts = df_train["tgt_lang"].value_counts().to_frame().reset_index()
lang_counts.columns = ["tgt_lang", "count"]
lang_counts["percentage"] = (lang_counts["count"] / lang_counts["count"].sum() * 100).round(2)
print(lang_counts.to_string(index=False))

Licensing

This dataset is released under the CC-BY-SA-4.0 license.

Citation

If you use this resource, please cite the dataset using its Hugging Face entry.

Repository: Tigre Parallel Multilingual Dataset Organization: BeitTigreAI URL: https://huggingface.co/datasets/BeitTigreAI/tigre-data-parallel-multilingual

Downloads last month
35