Datasets:

BeardedMonster
/

interlaanguage-translation

src_iso stringclasses 49 values	tgt_iso stringclasses 52 values	src stringlengths 2 4.62k	tgt stringlengths 3 4.18k	source_dataset stringclasses 93 values	licence stringclasses 3 values	licence_class stringclasses 3 values	provenance_kind stringclasses 4 values	lid_src int8 0 2	lid_tgt int8 0 2
pcm	tsn	I do pray for the pastor and the congregation.	Fa go ka nna le tuelo ya boikuelo, e tshwanetse go tla le boikuelo jo bo kwadilweng fa bo ya go Motlhankedi wa Tshedimosetso. Translate this sentence to sekwoa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
tsn	dag	Boagi jwa mo nageng le Bonno : Mo-Aforikaborwa	Citizenship and Residency : South African Translate to Tswana.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	1	2
pcm	tsn	How do you manage to make time for Him?	What's the Sekgoa translation for this text? lemogwa ge a bontsha boitsholo le kwano go bana ba gagwe.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	one of THEM.	mo thaeloñ, me u re gololè mo go eo o boshula. Translate to Seesimane.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	go to heaven when they die?	I need this sentence translated into sekgoa: A batho botlhe ba ba siameng ba ya legodimong fa ba swa?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	let's go to Copenhagen	Translate this text to eng for me: Bong ka bobedi bo a tshwana ka mmala.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Preach the Cross of Christ.	How do you translate this into eng? Ditlhwatlhwa di ne tsa fokodiwa thata	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	And no two days.	Could you provide the sekgoa translation for this? Rotlhe Katse	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
pcm	tsn	the Sound of Life	Translate this text to English for me: Setshwantshong sa Daniele, tshepe ke yona feela metale o kenwang ke mafome.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
pcm	tsn	I'm so glad I got to know this happy people!	What's the Eng translation for this text? Ga go nako e e beetsweng tirelo e.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	body temperature	thempereitšha ya mmele Please translate into sekgoa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
pcm	tsn	Can you help me by translating this to sekwoa? tuelo ya go rora	carriage	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	2
pcm	tsn	I'm from sunny South Africa	Ka re ke a go thusa o... What's the Seesemane translation?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Age 3 years old or older	Ka matlho Pelafalo o ne a bona e kete phaposi e e kgolonyana go gaisa ka moo a neng a akanya ka teng. Provide the Sekgoa translation.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Language from the start of the phase .	Could you provide the English translation for this? Puo ka tshimologo ya dikarolo .	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
tsn	dag	Could you translate the following into Seesimane? 25Moya o ikgohomosang o butswela dikgang; empa ya tshepang Jehova o tla kgora.	Published by Gospel Light, United States (2014)	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	0	2
pcm	tsn	I was born with Spina Bifida.	What's the seesemane translation for this text? Aborame a bo a humile thata, a na le diruiwa le selefera le gouta.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Yay you - go for it!!!	Translate this into english: le nna ha ke sa le monna wa hae.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
pcm	tsn	Because It's your work	Alhaji! ke itumelela kgakololo ya gago, le fa go ntse jalo, ke itse go menagane se ke se dirang, ga What's the Sekgoa translation?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Full-time student	What's the sekgoa translation for this text? Moithuti wa leruri	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Answers to The Question of Life	Could you provide the sekgoa translation for this? Barutwa ba gagwe ba utlwa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	I feel like I'm sick."	'I feel sick' - Ke ikutlwa e kare ke tla kgwa Translate this sentence to Sekgoa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Now you need to get use of.	Please translate the following sentence into eng: A o Reetsa Modimo?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	It's why we talk.	Translate this text to sekgoa for me: A ga lo ise lo lemoge, le fa e le go tlhaloganya?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Translate this text to Setswana for me: My wife and I talk about our money.	Nna le mosadi wa me re ne ra simolola go ngangisana ka madi.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	(Birds are searching for food.)	Translate this text to Sekwoa for me: (O a tswa, o tsamaya go batla dijo)	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Isaiah, 14 years old	How do you translate this into seesemane? Sri Lanka Polonnaruwa le site	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
tsn	bem	KAPA BOKONE Translate this to English.	NORTHERN CAPE	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	0	2
tsn	dag	Mme Charlotte Servais Please translate into Sekgoa.	The Charlotte Observer newspaper	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	0	2
pcm	tsn	My friends 2.	Ga ke ise ke ko ke boele kwa mekgweng eo. sekgoa translation needed.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	You're my only spiritual head	"Ke ne ke rata kitsi e e phepa. What's the sekgoa translation?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
tsn	dag	Could you provide the Sekgoa translation for this? ya kgatelelodiela	against Oppression.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	1	2
pcm	tsn	Some people come from far away	Ba bangwe ba tle ba tswa kgakala jaaka wa Gaborone. Translate this sentence to sekgoa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	only when I'm near you	Translate this into seesemane: Ere fa ke ntse gaufi le wena,	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Tiriso Translate this to english.	Application	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	2
pcm	tsn	All my friends for fun.	Re kaelwa ke se se builweng ke Madiba kwa kgotlatshekelo, ke mo nopola ka tlhamalalo: Translate to Sekgoa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	age group	What's the English translation for this text? ditlhopha tsa balekane	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Why they need to be equal?	Translate this text to Sekgoa for me: Gape Jakobe o ne a na le barwadi, mme Baebele e bua leina la a le mongwe fela wa bone.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Hope for All Mankind	Would you mind translating this into sekwoa? Go ne ga direga eng kwa Dijong Tsa Morena Tsa Maitseboa?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	kingdom of God - The Upper Room	Could you translate the following into Sekgoa? A ga se ene yo o mmatlang?	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	I like to help people get closer to Jehovah. Provide the Setswana translation.	Re itumelela go thusa ba bangwe go atamalana le Jehofa. - Math.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Where we find comfort.	Could you translate the following into Seesemane? 8 Nna ke lo kolobetsa ka metsi; mme ene o tla lo kolobetsa ka Mowa o o Boitshepo."	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	New York, and other	Could you translate the following into sekwoa? A re boneng seo fa re ntse re sekaseka pego e e mo go 1 Dikgosi 18:41-46.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	So, stop, and think.	"Leina la gagwe ke mang?" go ne ga botsa mongwe wa basimane. Translate this to sekgoa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	I'm rattling when I'm starting to lie	Can you help me by translating this to sekgoa? Gompieno dilo di fetogile.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Or look at the example of the apostle Paul.	Could you translate the following into Seesemane? le nngwe fa go tlhokega goya kwa phelelong.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Teach us to number our days (1)	Please translate the following sentence into Seesimane: Go amogela diphoso tsa me le go kopa maitshwarelo	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	All You 10.	What's the sekgoa translation for this text? Go matshwenedi gore UJ le yone e fitlhelletse makgaolakgang a monongwaga mmogo le TUT, feela dipalopalo di supa fa TUT ele bone bommamoratwa go ka fenya sejana sa monongwaga.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	I'm happy for you and you	boitumelo nawe Provide the Sekgoa translation.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	How to start to study the bible	O kae yo o neng a tsenwa ke mogopolo wa go dira jalo?" Please translate into seesemane.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	If possible, get outside of the workplace.	Give me the Eng translation of the following: Mme jaanong di mo kotsing.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Make time to listen to yourself.	What's the Sekwoa translation for this text? Iphe nako ya go itheetsa.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
pcm	tsn	He asks Jesus and no one else.	Could you translate the following into sekgoa? Ngobi ke e nngwe ya tsona.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
pcm	tsn	I'm still doing laundry	Could you translate the following into Sekgoa? o tla rerega thata,	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	0
tsn	dag	Motho o senya mpa fa a bolaya ngwana yo a iseng a tsholwe. Sekgoa translation needed.	Developed in May 2019	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	1	2
pcm	tsn	Because we are all sheep.	Romela Romela A lo Dumela Gore Bodumedi Jwa Lona ke Jone Fela Jwa Boammaaruri? english translation needed.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	It's come from west Africa.	VPR: Mme la Presidente Eng translation needed.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Explanation or example	How do you translate this into seesemane? Tlhaloso kgotsa sekai	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	I'm from New york..	Ke tswa kwa New York = I am from New York. Translate this to English.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	Either you work for yourself or for someone else .	What's the seesemane translation for this text? O ka nna wa ipereka kgotsa wa berekela motho yo mongwe .	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
pcm	tsn	setori Translate this to english.	floor	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	2
pcm	tsn	Not too young to serve God	I need this sentence translated into english: O tla go thusa go tlhaloganya Dikwalo.	OxxoCodes/pulabert-dataset	unknown	unspecified	mixed	2	1
swh	mlg	Tizita Hagere (kulia) akicheza nafasi ya Hirut Assefa mwenye umri wa miaka 14 kwenye filamu ya 'Difret.'	Tizita Hagere (havanana) no nitàna ny toeran'i Hirut Assefa, 14 taona, ao anatin'ny 'Difret.'	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
som	tir	Xabsiga ayaa laga siidaayay atariishada reer Iran Marzieh Vafamehr kadib markii laga yareeyay xukunkii ay ku mutashay xadhiga ee ahaa filimkii la mamnuucay ee My Tehran for Sale	ኢራናናዊት ተዋሳኢት ማርዚዬ ቫፋሜህር ኣብቲ ብሕጊ ዝተኸልከለ ቴህራን ከተማይ ንመሸጣ ዝብል ፊልም ብምውሳኣ ተፈሪዱዋ ዝነበረ ፍርዲ ምስተነከየ ካብ ማእሰርቲ ተለቒቓ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Waaqayyo Tajaajilaa isaa erga muudee booda, tokkoon tokkoon keessan hojii keessan isa hamaa irraa isin deebisee isin eebbisuuf jalqaba gara keessanitti isa ergeera.”	አምላክ አገልጋዩን ካስነሳ በኋላ እያንዳንዳችሁን ከክፉ ሥራችሁ በመመለስ ይባርካችሁ ዘንድ በመጀመሪያ ወደ እናንተ ላከው።”	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	ከዚያም ከመቅደሱ ውጭ፣ በቤተ መቅደሱ ውስጥ ለዚህ ተብሎ በተመደበው ቦታ ታቃጥለው ዘንድ የኃጢአት መባ የሆነውን ወይፈን ውሰድ።	ሽዑ፡ ነቲ ዝራብዕ፡ ነቲ መስዋእቲ ሓጢኣት ኣብቲ ምዱብ ቦታ እታ ቤተ መቕደስ፡ ኣብ ወጻኢ እታ መቕደስ ምእንቲ ኸተንድዶ፡ ውሰዶ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
som	amh	Kanada ayaa cadaysay in BPA ay sun tahay, taasoo keentay in la joojiyo ama laga mamnuuco kiimikada aadka loo isticmaalo.	ካናዳ በሰፊው ጥቅም ላይ የሚውለው ኬሚካል ቢፒኤ መርዛማ እንደሆነ በማወጅ እገዳዎች እንዲደረጉ ታበረታታለች።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
swh	mlg	Alidhalilishwa na vijana wa kiume akiwa njiani.	Notohintohinin'ny tovolahy sasantsasany izy teny an-dalana.	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	2
swh	mlg	Sheria mpya inawataka vijana kujali “mahitaji ya kiroho” na “kutowapuuza wazee” lakini sheria hii haijaweka bayana ni mara ngapi vijana wanapaswa kuwatembelea wazazi wao au ni adhabu gani watakabiliana nayo endapo watashindwa kuitii sheria hii.	" Milaza io lalàna vaovao io fa tokony hikarakara ny ""zavatra ara-panahy ilain'ny ray aman-dreniny"" ny olon-dehiba ary ""tsy hanao tsinontsinona ireo antitra"", nefa tsy manamaritra ny fotoana hitsidihan'izy ireo ny ray aman-dreniny izany na ny sazy ho azon'izy ireo raha tsy voahaja izany. "	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	tir	Faayidaan galateeffachuun barataa tokkoof qabu, faayidaa bishaan biqiltuudhaaf argamsiisuu wajjin wal fakkaata; guddina akka argisiisu isa gargaara.	ልክዕ ከምቲ ማይ ንሓንቲ ተኽሊ ንኽትለምዕ ዚሕግዛ፡ ልባዊ ናእዳ እውን ንሓደ ዚስልጥን ሓው ዕቤት ንኺገብር ይሕግዞ እዩ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Hamma dandeenye wantoota foonii fi wantoota hafuuraa namoota kaaniif arjummaadhaan kennuudhaan Yesus irraa akka baranne argisiisna.	አዎ፣ አቅማችን በፈቀደ መጠን ለሌሎች ቁሳዊም ሆነ መንፈሳዊ ነገሮችን በልግስና በማካፈል የኢየሱስን ምሳሌ መከተል እንችላለን።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Kun, Yihowaan miira warra kaanii akka hubatu argisiisa; nuufis dandeettii kana nuu kenneera.	በሌላ አባባል ይሖዋ ራሱን በሌሎች ቦታ አድርጎ መመልከት ይችላል፤ ይህንን ችሎታ ለእኛም ሰጥቶናል።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	ጌታዬ ንጉሥ ሆይ፣ እባክህ የአገልጋይህን ቃል ስማ፦ በእኔ ላይ እንድትነሳ ያደረገህ ይሖዋ ከሆነ የማቀርበውን የእህል መባ ይቀበል። ሆኖም እንዲህ እንድታደርግ ያነሳሱህ ሰዎች ከሆኑ በይሖዋ ፊት የተረገሙ ይሁኑ፤ ምክንያቱም ‘ሂድ፣ ሌሎች አማልክትን አገልግል!’ ብለው በይሖዋ ርስት ውስጥ ድርሻ እንዳይኖረኝ ዛሬ አባረውኛል።	በጃኻ ጐይታይ ንጉስ፡ ዘረባ ጊልያኡ ይስማዕ፦ እቲ ኣንጻረይ ዝደፋፍኣካ የሆዋ እንተ ዀይኑ፡ መስዋእቲ እኽለይ ይቀበል። ደቂ ሰብ እንተ ደፋፊኦምኻ ግና፡ ምስ ርስቲ የሆዋ ሓድነት ከይህልወኒ፡ ‘ኪድ፡ ንኻልኦት ኣማልኽቲ ኣገልግል’ ኢሎም ሎሚ ሰጒጎምኒ እዮም እሞ፡ ኣብ ቅድሚ የሆዋ ርጉማት ይኹኑ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
swh	mlg	Mchoro mdogo ukionesha aina mbili za matambiko ya jamii mbili tofauti.	Sary kely an-dridrina maneho karazana fomba roa fanaon'ny vondrona roa samihafa.	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	በእርግጥም የሰው ጠላቶቹ የገዛ ቤተሰቦቹ ይሆናሉ።	ንሰብ ከኣ ቤተ ሰቡ ጸላእቱ ኪዀኑ እዮም።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	2
swh	mlg	Kama alivyosema mwanamke mmoja aitwaye Selvi, “hii ni mara tu baada ya kuwa miongoni mwa sehemu ya kujituma ndipo tulipogundua kuwa kujaribu kuweka misingi ya haki ya mtu ya kuishi kama mtu anavyotegemea, akiendeleza utamaduni wa kuishi kindugu na pia kuhoji mambo yanayotekelezwa bila hata ya kujadiliana na watu ni kar...	Hoy ny vehivavy iray hafa, Selvi, nilaza, “ Taorian'ny fandraisana anjara tamin'ny tolona no nahafantaranay fa ny fiezahana hametraka ny zony hiaina araka ny faniriany, ny miaina araka ny fiainana nenti-paharazana ary ny manontany ny amin'ireo karazan-draharaha tsy nangalana ny hevitry ny vahoaka dia mitovy amin'ny fam...	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Yesuus kana yommuu dhagaʼu akkana isaaniin jedhe: “Namoota dhukkubsataniif malee, namoota fayyaadhaaf ogeessi fayyaa hin barbaachisu. Ani namoota qajeeloo utuu hin taʼin, cubbamoota waamuufan dhufe.”	ኢየሱስ ይህን ሲሰማ “ሐኪም የሚያስፈልጋቸው ሕመምተኞች እንጂ ጤነኞች አይደሉም። እኔ የመጣሁት ጻድቃንን ሳይሆን ኃጢአተኞችን ልጠራ ነው” አላቸው።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	“Ani isinitti nan hima, nama namoota duratti dhugaa anaaf baʼu hundumaatiif, Ilmi namaa immoo maleekota Waaqayyoo duratti dhugaa isaaf baʼa.	“እላችኋለሁ፣ በሰዎች ፊት የሚመሠክርልኝን ሁሉ የሰው ልጅም በአምላክ መላእክት ፊት ይመሠክርለታል።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	ሞኞች በከፍተኛ የሥልጣን ቦታዎች ላይ ሲቀመጡ የናጠጡ ሀብታሞች ግን በዝቅተኛ ቦታዎች ላይ ይገኛሉ።	ዕሽነት ኣብ ሓያሎ ልዑል ቦታታት ተቐሚጡ ኣሎ፣ ሃብታማት ግና ኣብ ትሑት ቦታታት ይነብሩ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Isaan foʼaa fiixee uffata isaa qofa tuquuf illee isa kadhatu turan; warri foʼaa fiixee uffata isaa tuqan hundis guutummaatti ni fayyan.	የልብሱን ዘርፍ ብቻ እንኳ ለመንካት ይማጸኑት ነበር፤ የነኩትም ሁሉ ሙሉ በሙሉ ተፈወሱ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Gooftaa Yihowaan guyyaa sanatti gara laafina isaa isatti haa argisiisu. Tajaajila inni Efesoon keessatti raawwate hundas akka gaariitti beekta.	ጌታ ይሖዋ በዚያ ቀን ምሕረቱን ይስጠው። ደግሞም በኤፌሶን ያከናወነውን አገልግሎት ሁሉ በሚገባ ታውቃለህ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	“ኤፍሬም በተናገረ ጊዜ ሰዎች ተንቀጠቀጡ፤በእስራኤል ነገዶች መካከል ትልቅ ቦታ ነበረው። ሆኖም ባአልን በማምለክ በደል በመፈጸሙ ሞተ።	“ኤፍሬም ምስ ዚዛረብ፡ ራዕራዕታ ይኸውን ነይሩ፣ኣብ እስራኤል ምርኡይ ነይሩ። ግናኸ፡ ምስ በዓል ብእተተሓሓዘ በዲሉስ ሞይቱ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
swh	som	22 Tena itakuwa mtaigawanya kwa kura, kuwa urithi kwenu, na kwa wageni wakaao kwenu hali ya ugeni, watakaozaa watoto kati yenu, nao watakuwa kwenu, kama wazaliwa miongoni mwa wana Israeli; watakuwa na urithi pamoja nanyi kati ya kabila za Israeli.	22 Oo waa inaad dhaxal ahaan saami ugu qaybsataan idinka iyo shisheeyayaasha idin dhex deggan oo dhexdiinna carruurta ku dhalay, oo waxay idiin ahaan doonaan sida kuwa dalka ku dhex dhashay oo reer binu Israa'iil oo kale, oo iyaguna waa inay dhaxal idinkula qaataan qabiilooyinka reer binu Israa'iil dhexdooda.	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	ሁለቱ በሮች ከጥድ እንጨት የተሠሩ ነበሩ፤ በበሮቹም ላይ የኪሩቦችን፣ የዘንባባ ዛፎችንና የፈኩ አበቦችን ምስል ቀረጸባቸው፤ በወርቅም ለበጣቸው፤ ደግሞም ወርቁን በኪሩቦቹና በዘንባባ ዛፎቹ ላይ ጠፈጠፈው።	እተን ክልተ ማዕጾ ኻብ ዕንጨይቲ ጽሕዲ ነበራ፣ ኣብአን ከኣ ኪሩቤልን ኣእዋም ስየን ዝዓምበበ ዕምባባታትን ቀረጸ፣ ብወርቂ እውን ለበጠን። ነቲ ወርቂ ኣብ ልዕሊ እቶም ኪሩቤልን እቲ ኣእዋም ስየን ቀጥቂጡ ዘርግሖ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
som	tir	Liu Xiaobo ololeeye siyasi Shiine ah kuna guuleystay abaalmarinta Nobel Peace Prize ayaa xabsiga laga sii daayay cafimaad cafimad daro kadib markii laga helay kansarka beerka ee dilaaga ah.	ቻይናዊ ኣበራባሪ ፖለቲካን ተዓዋቲ ሽልማት ሰላም ኖቤልን ሊዩ ሺያቦ ዘይድሕን መንሽሮ ጉበት ከምዝሓዞ ምስተረጋገፀ ሕክምናዊ ምሕረት ተገይሩሉ ካብ ማእሰርቲ ተፈቲሑ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
swh	mlg	Na kuanzia hapo akapa wazo la kuwapiga picha watumishi wa afya na kuziweka kwenye mavazi hayo ya kujilinda na maambukizi.	Ka nitsiry taminy ny hevitra haka ny sarin'ireo mpiasan'ny fahasalamana izay mety miraikitra amin'ny fitafiana fiarovan'izy ireo.	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	tir	Warri haaraan obboloota isaanii gargaaruun barbaachisaa taʼuu isaa akka hubatan gargaaruu kan dandeenyu akkamitti?	ሓደስቲ ኣስፋሕቲ ንኣሕዋቶምን ንኣሓቶምን ምሕጋዝ ዘለዎ ኣገዳስነት ምእንቲ ኺግንዘቡ፡ ብኸመይ ክንሕግዞም ንኽእል፧	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	የአምላክህን ምግብ የሚያቀርበው እሱ ስለሆነ ቀድሰው። እናንተን የምቀድሳችሁ እኔ ይሖዋ ቅዱስ ስለሆንኩ እሱም በአንተ ፊት ቅዱስ ሆኖ መገኘት አለበት።	ንሱ እንጌራ ኣምላኽካ የቕርብ እዩ እሞ፡ ቀድሶ። ዝቕድሰኩም ኣነ የሆዋ ቕዱስ እየ እሞ፡ ንሱ ቕዱስ ይኹነልኩም።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	ይሖዋ ሆይ፣ ከጥንት ጀምሮ የነበሩትን ፍርዶችህን አስታውሳለሁ፤በእነዚህም መጽናኛ አገኛለሁ።	ኦ የሆዋ፡ ናይ ጥንቲ ፍርድታትካ እዝክር፡ብእኡ ድማ እጸናናዕ እየ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Yaaqoob akkana jedhee barreesseera: Amantii kee hojii irraa addaan baasii natti argisiisi, ani immoo amantii koo hojiidhaan sitti nan argisiisa.	ያዕቆብ እምነትህን ከሥራ ለይተህ አሳየኝ፤ እኔ ደግሞ እምነቴን በሥራ አሳይሃለሁ በማለት ጽፏል።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	tir	Mootummootta Gamtoomanitti Ambasaaddarri Yunaayitid Isteetis, Suuzaan Raayis, Gaadaafiin guddeeddii hedduminaan akka raawwataniif humnoota waraanaa isaaf viyaagiraa dhiyeessaa jedhan.	ጋዳፊ ሓይልታቱ ምእንታን ጃምላዊ ፆታዊ ምግሃስ ክፍፅሙ ቪያግራ የቕርበሎም እዩ ክትብል ኣብ ሕቡራት መንግስታት ኣምበሳደር ዩናይትድ ስቴትስ ሱዛን ራይስ ከሲሳ ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
som	orm	Gobollada xeebaha badweynta Atlantika ee Kanada aya u diyaargaroobaya baraf la saadaaliyay in uu noqon doonoo duufaantii ugu xumayd muddo toban sano ah.	Kutaalee biyyaa daangaa Atilaantik Kanaadaa, bubbee hobonboleettii arfaasaa kan waggoota kudhan keessatti hobonboleettii isa hamaa jedhamuun tilmaamamuuf of qopheessan.	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Kanaan kan kaʼes, ani ‘Isaan gara boqonnaa kootti hin galan’ jedhee aarii kootiin nan kakadhe.”	በመሆኑም ‘ወደ እረፍቴ አይገቡም’ ብዬ በቁጣዬ ማልኩ።”	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
som	tir	Waxa uu xusay in isticmaalka Kiimikada warshadaha ee Itoobiya ay u baahan tahay nidaam maamul oo adag si loo ogaado sida loo isticmaalo ama loo tuuro kiimikada.	ኣብዚ ሕዚ እዋን ኣብ ኢትዮጵያ ዘሎ ኣጠቓቕማ ኢንዱስትሪያዊ ኬሚካል ንኬሚካል ብኸመይ ምጥቃም ወይ ምውጋድ ከምዝከኣል ከፈልጡ ዝሕግዞም ድልዱል ምምሕዳራዊ ስርዓት የድልዮ እዩ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	Yesuus karaa akka gad of deebisu argisiisuun kan dubbate, dhaggeeffattoonni isaa wanti inni dubbatu beekumsaa fi ogummaa ofii isaa irratti kan hundaaʼe utuu hin taʼin, Yihowaa biraa kan dhufe akka taʼe akka beekan waan barbaaduuf ture.	ኢየሱስ በንግግሩ ልኩን እንደሚያውቅ አሳይቷል፤ ይህን ያደረገው አድማጮቹ የሚናገረው ነገር በራሱ እውቀትና ጥበብ ላይ የተመሠረተ ሳይሆን ከይሖዋ የመጣ እንደሆነ እንዲያውቁ ይፈልግ ስለነበር ነው።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
amh	tir	በመቀጠልም ከዲቦንጋድ ተነስተው በአልሞንዲብላታይም ሰፈሩ።	ካብ ዲቦን-ጋድ ነቒሎም ከኣ፡ ኣብ ዓልሞን-ዲብላታዪም ሰፈሩ።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
swh	som	4 Nikamwona huyo kondoo mume akisukuma upande wa magharibi, na upande wa kaskazini, na upande wa kusini; wala hakuna mnyama ye yote awezaye kusimama mbele yake, wala hakuna mnyama ye yote awezaye kupokonya mkononi mwake; lakini alitenda kama alivyopenda mwenyewe, akajitukuza nafsi yake.	4 Oo waxaan arkay wankii oo wax u riixaya xagga galbeed iyo xagga woqooyi, iyo xagga koonfureed, oo bahalna ma hor istaagi karin, mana jirin mid gacantiisa wax ka bixin karay; laakiinse siduu doonayay ayuu yeeli jiray, wuuna isweyneeyey.	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	amh	akkasumas, sagalee malakataa fi sagalee Waaqayyoo isa namoonni sun yommuu dhagaʼan sana caalaa akka isaanitti hin dubbatamne kadhatan sanatti hin dhihaanne.	ወደ መለከት ድምፁና ቃል ያሰማ ወደነበረው ድምፅ አይደለም፤ ሕዝቡ ይህን ሲሰሙ ሌላ ተጨማሪ ነገር እንዳይነገራቸው ለምነው ነበር።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
orm	tir	Pirasdaantiin Maalii duraanii Amaduu Toomanii Tuuree fonqolcha waraanaan erga aangoo irraa buufamee booda Seenegaal gahe.	ፕሬዚደንት ነበር ማሊ ኣማዲ ቱማኒ ቱሬ ብወተሃደራዊ ዕልዋ ድሕሪ ምእላዮም ሴኔጋል ኣትዮም።	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1
swh	mlg	Basi lililokuwa limebeba watu 40, wengi wao wakiwa ni wanafunzi wa shule ya msingi na walimu wao, liliangukia mtoni mkoani Arusha, kaskazini mwa Tanzania, na kuua watu wasiopungua 31, kwa mujibu wa taarifa za habari.	Nidoboka tany amin'ny renirano tao Arusha, Tanzania avaratra, ny bus iray mitondra olona 40, ary mpianatry ny fanabeazana fototra sy ny mpampianatra ary ireo no ankamaroan'ireo, ary farafahakeliny 31 no maty, araka ny tati-baovao.	UBC-NLP/AfroLingu-MT	unknown	unspecified	human_curated	1	1

End of preview. Expand in Data Studio

interlaanguage-translation: African language X -> African language Y

Training data for a direct (no English pivot) inter-African-language translation model: sentence-pair windows between 77 African languages (SFT) and monolingual source windows with a target-language tag (RL prompts). The 77 languages are listed in direction_counts.csv (ISO 639-3 style tags in the src_iso / tgt_iso columns; the YAML header lists only those with a two-letter code). Built from the data of the English -> African translation model (gemma_mt, D-46 in the project's DECISIONS.md).

IMPORTANT: licences

Every row keeps the licence of the source it was taken from. The licence column holds the licence declared on the source dataset's card (unknown when the card declares none; we never guess one). A pair that joins two sources shows both, a + b. Some rows are non-commercial, share-alike or of unknown licence; the dataset as a whole is therefore NOT under one licence. Check the licence and source_dataset columns and filter before you use the data (for commercial use keep only the licences you may use; for CC-BY-SA material keep the share-alike obligation). licence_class is the coarser class used by the build (cc-by, share_alike, unspecified, ...). Reported licence distribution of the SFT training pairs:

33.7 % of the SFT training rows have at least one side whose licence is unknown, 3.4 % one side declared other. No source in these rows declares a non-commercial licence (sources with NC licences were dropped by the en->X build, D-21), but the original texts behind some sources (JW / Bible material of the OPUS-MT560 sets) carry copyright of their own that the dataset cards do not clear.

`licence`	rows	share
cc-by-4.0	4,287,634	62.66%
unknown	1,229,762	17.97%
unknown + cc-by-4.0	873,345	12.76%
cc-by-4.0 + unknown	141,267	2.06%
other + cc-by-4.0	135,954	1.99%
mit	53,761	0.79%
unknown + other	30,387	0.44%
other	24,291	0.36%
cc-by-4.0 + other	20,378	0.30%
other + unknown	18,823	0.28%
mpl-2.0	9,216	0.13%
cc-by-sa-4.0	6,294	0.09%
mpl-2.0 + unknown	4,946	0.07%
unknown + mit	1,363	0.02%
apache-2.0 + cc-by-4.0	1,362	0.02%
apache-2.0 + unknown	1,258	0.02%
unknown + apache-2.0	701	0.01%
unknown + mpl-2.0	379	0.01%
apache-2.0 + other	267	0.00%
cc-by-4.0 + apache-2.0	239	0.00%
cc-by-sa-4.0 + unknown	167	0.00%
mit + unknown	139	0.00%
other + apache-2.0	78	0.00%
cc-by-sa-4.0 + cc-by-4.0	71	0.00%
mpl-2.0 + cc-by-4.0	58	0.00%

Files

file	rows	content
rl_prompts.parquet	509,488	RL prompts: source-language window + target tag
sft_pairs_train.parquet	6,842,249	SFT sentence pairs, one row per UNORDERED pair {src_iso, tgt_iso} (train a model on both directions)
sft_pairs_val.parquet	81,760	validation pairs (whole English sentences held out, never used with another partner in train)

What is in a row (SFT pairs)

src_iso, tgt_iso (ISO-639-3 style tags of gemma_mt/languages.py, src_iso sorts before tgt_iso), src, tgt (NFC text, windows of consecutive sentences are made at training time), pivot_en (the English sentence both sides translate, null for direct pairs), origin (pivot_en = two translations of the same English sentence; direct = a corpus that already pairs the two languages; mined_nllb = NLLB-v1 mined pair, filtered, non-commercial upstream), provenance_kind (human_curated | mined_nllb | mixed | religious_jw | synthetic_mt: a name-pattern heuristic, not an audit), prompt_form, source_dataset, licence, licence_class, qe_src / qe_tgt (AfriCOMET-QE of the English -> X translation of each side, NaN for direct pairs), group_size (number of languages that share the English sentence), group_key, src_tok / tgt_tok (Gemma tokens), epochs (how often the build planned to repeat the pair).

Composition

SFT train pairs: 6,842,249; ordered directions with data: 5622 of 5852; with >= 1,000 pairs: 4104; >= 100 pairs: 4792. Per-direction counts: direction_counts.csv.
Sampling: UniMax over the unordered language pairs (uniform share of the budget, at most 3 passes over a pair's own data), so no rich pair dominates; the cap per language pair is a few thousand sentence pairs (<= 3.9 k).
Domain warning: most multi-way material comes from Bible / JW-style parallel text (see provenance_kind); government text (South African languages), news and community corpora are a small share.
The matching packed token dataset (not in this repo): 8,205,636 samples, 1,691,160,438 Gemma tokens, seq_len 4096; directions {'en2x': 1033766, 'x2en': 1033766, 'x2x': 6138104}; prompt forms {'explicit': 4101804, 'implicit': 4103832}.

RL prompts

rl_prompts.parquet: 509,493 prompts staged (before the private-source exclusion), one source-language window with a target tag, 5852 ordered directions (median 116 prompts per direction, minimum 3). Columns: source, src_iso, iso (target), language, src_language, src_afr_tokens (AfroXLM-R tokens), length_bin (b64 / b256 / b512 / b1024), n_sentences, source_dataset, licence, licence_class, src_qe_valid, tgt_qe_valid. Sources: real documents (HuggingFaceFW/fineweb-2, ODC-By-1.0; amh hau ibo pcm tir yor) and, for every language, text of the en->X corpus that is held out of the SFT pairs (neither the text nor its English sentence is in any SFT pair). Thin pools (kea, her, ish, wes, dua, oke, dyu, ibb) have only a handful of windows each and are reused many times.

`full_pairs/`: the complete pair set (not a sample)

The files above are the SAMPLED training set (UniMax, a few thousand pairs per language pair). full_pairs/ holds everything we could derive, sharded parquet (zstd), every row with source_dataset, licence, licence_class; the held-out evaluation sets and the rows of private source repositories are excluded exactly as above. One row per UNORDERED pair {src_iso, tgt_iso} (src_iso sorts before tgt_iso); a model uses both directions, so the number of ordered pairs is twice the number of rows. Nothing is sampled or thresholded: the quality signals are columns (qe_*, lid_*, provenance_kind, score), filter on them.

folder	rows (unordered pairs)	ordered pairs	content
`full_pairs/pivot_en/<src_iso>/part-*.parquet`	50,824,383	101,648,766	two translations of the same English sentence (join of the en->X corpus on the normalised English text); `group_key` links to `full_pairs/pivot_en_sentences.parquet` (1,552,726 English sentences); `in_sft` marks the pairs selected for the sampled SFT files
`full_pairs/direct/direct_pairs.parquet`	1,053,147	2,106,294	pairs of the SFT corpus that already pair two African languages (53 % machine translation, `provenance_kind` tells)
`full_pairs/nllb_mined/<src>-<tgt>.parquet`	105,658,159	211,316,318	NLLB-v1 mined pairs republished as `michsethowusu/<lang>-<lang>_sentence-pairs` (526 shards; a few language pairs have a second shard `__<repo>` from a second repo). No licence is declared on those cards; treated as non-commercial upstream; raw mined data with a margin `score`, NOT filtered for quality or language

Held-out removal in full_pairs: 931 en->X rows (their pairs) matched an evaluation sentence by the 8-gram rule on top of the exact rule applied earlier; private-source rows removed: 53,449. Mined pairs dropped for a held-out match: 17,621. Mined rows with an empty side are dropped (one repo, swahili-zulu, ships an empty Zulu column and is absent; akan-twi pairs a language with itself and is absent).

Pivot pairs by provenance kind: synthetic_mt 1,537,968, mixed 12,533,012, religious_jw 36,360,612, human_curated 392,791.

Licence distribution of full_pairs/pivot_en (declared licence, rows):

licence	rows
cc-by-4.0	35,219,023
unknown + cc-by-4.0	10,905,665
unknown	2,420,013
cc-by-4.0 + unknown	905,031
other + cc-by-4.0	496,014
unknown + other	229,563
mit	205,319
other	151,262
other + unknown	122,174
cc-by-4.0 + other	66,498
mpl-2.0	40,419
cc-by-sa-4.0	21,897
mpl-2.0 + unknown	15,638
unknown + mit	10,716
unknown + mpl-2.0	5,880

full_pairs/direct licences: unknown 968,491, cc-by-4.0 84,637, other 19.

Sizes on disk: pivot_en 4.12 GB, direct 0.14 GB, nllb_mined 7.77 GB, pivot_en_sentences 0.09 GB.

RL prompts v2 (more real documents)

Source windows now also come from open web corpora streamed from the Hub (HuggingFaceFW/fineweb-2, cis-lmu/GlotCC-V1, HPLT/HPLT2.0_cleaned, wikimedia/wikipedia 20231101, allenai/c4 multilingual), filtered by GlotLID, de-duplicated and held out from the SFT pairs and the benchmarks; real documents are preferred over pseudo-paragraphs of translated sentences. Windows kept per source language (b64 + b256 + b512 + b1024) before -> after:

language	before	after
yor	6,000	6,000
hau	6,000	6,000
ibo	6,000	6,000
pcm	4,979	5,579
efi	5,298	6,000
twi	6,000	5,564
ewe	3,865	6,000
fon	5,348	5,568
wol	4,674	5,874
swh	4,307	6,000
kin	5,588	6,000
som	5,566	5,994
orm	5,466	6,000
amh	6,000	6,000
tir	6,000	6,000
lug	4,477	6,000
lin	3,841	5,907
zul	5,313	4,727
xho	5,287	6,000
afr	4,391	6,000
sna	5,322	2,220
nya	5,509	4,254
sot	5,685	5,768
tsn	5,307	6,000
mlg	5,259	5,887
ibb	150	3,511
urh	358	721
bem	3,839	3,306
tum	2,286	4,747
run	3,245	6,000
ven	2,417	4,691
tso	4,937	6,000
nso	5,419	6,000
ssw	1,693	5,024
nbl	5,179	5,911
sag	3,095	6,000
tiv	2,755	3,855
umb	2,300	3,250
kmb	1,726	2,678
mos	2,932	4,122
kik	1,071	3,758
luo	4,589	4,968
kam	388	1,291
bin	3,299	3,487
dag	3,521	4,273
oke	95	139
shi	617	946
dyu	102	2,781
bam	1,065	4,086
kbp	434	4,362
bbj	520	526
kon	139	2,013
kea	8	2,547
kab	4,101	6,000
nus	5,508	5,582
swc	4,740	6,000
lua	3,953	5,198
kqn	3,176	3,424
lun	1,579	1,580
iso	3,469	4,282
loz	5,359	5,833
wal	1,858	3,896
ach	1,033	2,294
tsc	1,313	1,537
vmw	1,315	1,871
kua	1,153	3,946
seh	695	1,363
nyn	708	1,747
her	22	1,063
yao	457	742
sid	249	931
ndc	407	909
kri	651	728
ish	24	68
dua	67	277
bas	271	474
wes	35	54

Prompt forms (SFT)

prompt_form (explicit | implicit) is a deterministic function of the pair (blake2b of group_key|src_iso|tgt_iso, 50 % each): explicit = Translate the text from {source} to {target}: {text}, implicit = Translate the text to {target}: {text} (the en->X-compatible form). The answer is always {target tag} {translation}.

Filters

English sentence must be English and the African side must pass GlotLID for its language (where LID is reliable); per-language floor on the AfriCOMET-QE of the English -> X translation (30th percentile on top of the build's 15 % gate); length-ratio window per language pair; no copy of the source (identical, or word-set Jaccard >= 0.9); script check (Ethiopic languages); URL / markup debris removed; de-duplication on the text pair; validation = whole English-sentence groups.

Held-out evaluation data (NOT in this dataset)

Nothing from these sets is in any file, by exact match after normalisation (any language) and by word-8-gram overlap: FLORES+ dev and devtest, NTREX-128, Google SMOL (SmolSent, SmolDoc, GATITOS), MAFAND-MT test, IbomMT, FLORES-MOZ, GlotStoryBook, SALT test, and the documents of the project's long-document benchmark. They are the benchmarks of the models trained on this data.

Private / personal data

No personal data is knowingly included. Rows taken from source repositories that are flagged private in the build's licence scan were not staged for this repository (45,024 rows).

Sources (`source_dataset`, rows in the SFT training pairs)

source_dataset	rows
dsfsi/govza-sa-cabinet-statements-sentence-aligned	101,976
Tadesse/COMET_score	53,761
michsethowusu/african-bible-parallel	43,785
dsfsi/afriscience_mt	35,610
dsfsi/vukuzenzele-sentence-aligned	27,571
BeardedMonster/sft-new	24,272
MaLA-LM/PolyWrite	22,729
UBC-NLP/AfroLingu-MT	19,542
BeardedMonster/naija2 + BeardedMonster/sft-new	18,031
Okwu/african-language-parallel-corpus	9,528
ayymen/Pontoon-Translations	9,216
Mehgoss/sa-languages-translation	8,752
BeardedMonster/naija + michsethowusu/english-lozi_sentence-pairs_mt560	8,381
BeardedMonster/naija + michsethowusu/english-luba-kasai_sentence-pairs_mt560	8,164
BeardedMonster/naija2	7,842
BeardedMonster/naija + michsethowusu/english-isoko_sentence-pairs_mt560	7,813
BeardedMonster/naija + michsethowusu/english-kaonde_sentence-pairs_mt560	7,593
BeardedMonster/sft-new + BrianMwangi/english-to-luo-opus	7,571
BeardedMonster/naija + michsethowusu/english-wolaytta_sentence-pairs_mt560	6,952
BeardedMonster/naija + michsethowusu/english-lunda_sentence-pairs_mt560	6,890
BeardedMonster/naija + michsethowusu/english-dholuo_sentence-pairs_mt560	6,788
BeardedMonster/sft-new + michsethowusu/english-lozi_sentence-pairs_mt560	6,714
BeardedMonster/naija + michsethowusu/english-sango_sentence-pairs_mt560	6,678
BeardedMonster/naija + michsethowusu/english-oshiwambo_sentence-pairs_mt560	6,645
BeardedMonster/naija2 + michsethowusu/english-luba-kasai_sentence-pairs_mt560	6,594
BeardedMonster/naija + michsethowusu/english-venda_sentence-pairs_mt560	6,571
BeardedMonster/naija + michsethowusu/english-moore_sentence-pairs_mt560	6,547
BeardedMonster/naija + michsethowusu/english-tiv_sentence-pairs_mt560	6,461
BeardedMonster/sft-new + michsethowusu/english-wolaytta_sentence-pairs_mt560	6,421
BeardedMonster/naija + michsethowusu/english-congo-swahili_sentence-pairs_mt560	6,395
BeardedMonster/naija2 + michsethowusu/english-lozi_sentence-pairs_mt560	6,340
McGill-NLP/SSA-MTE	6,294
BeardedMonster/naija + michsethowusu/english-sidaama_sentence-pairs_mt560	6,289
BeardedMonster/naija + michsethowusu/english-yao_sentence-pairs_mt560	6,257
BeardedMonster/naija + michsethowusu/english-northern-sotho_sentence-pairs_mt560	6,224
BeardedMonster/naija2 + michsethowusu/english-isoko_sentence-pairs_mt560	6,183
BeardedMonster/naija + michsethowusu/english-okpe_sentence-pairs_mt560	6,106
BeardedMonster/naija + michsethowusu/english-basaa_sentence-pairs_mt560	6,099
BeardedMonster/naija2 + michsethowusu/english-kaonde_sentence-pairs_mt560	5,941
BeardedMonster/naija + michsethowusu/english-acholi_sentence-pairs_mt560	5,915
BeardedMonster/naija + michsethowusu/english-tswa_sentence-pairs_mt560	5,890
BeardedMonster/naija + michsethowusu/english-swati_sentence-pairs_mt560	5,873
BeardedMonster/naija + michsethowusu/english-nyankore_sentence-pairs_mt560	5,873
BeardedMonster/naija + michsethowusu/english-tumbuka_sentence-pairs_mt560	5,822
BeardedMonster/naija + michsethowusu/english-makhuwa_sentence-pairs_mt560	5,800
BeardedMonster/naija + michsethowusu/english-sena_sentence-pairs_mt560	5,783
BeardedMonster/naija + michsethowusu/english-gikuyu_sentence-pairs_mt560	5,753
BeardedMonster/sft-new + michsethowusu/english-kaonde_sentence-pairs_mt560	5,715
BeardedMonster/naija2 + michsethowusu/english-congo-swahili_sentence-pairs_mt560	5,711
BeardedMonster/naija + michsethowusu/english-rundi_sentence-pairs_mt560	5,684
BeardedMonster/naija + michsethowusu/english-ganda_sentence-pairs_mt560	5,648
BeardedMonster/naija + michsethowusu/english-krio_sentence-pairs_mt560	5,600
BeardedMonster/naija + michsethowusu/english-umbundu_sentence-pairs_mt560	5,587
BeardedMonster/naija + michsethowusu/english-bemba_sentence-pairs_mt560	5,467
BeardedMonster/naija + michsethowusu/english-malagasy_sentence-pairs_mt560	5,434
BeardedMonster/sft-new + michsethowusu/english-congo-swahili_sentence-pairs_mt560	5,399
BeardedMonster/naija2 + michsethowusu/english-setswana_sentence-pairs_mt560	5,392
BeardedMonster/naija + michsethowusu/english-duala_sentence-pairs_mt560	5,344
BeardedMonster/naija2 + michsethowusu/english-venda_sentence-pairs_mt560	5,338
BeardedMonster/sft-new + michsethowusu/english-luba-kasai_sentence-pairs_mt560	5,258

The full list is in MANIFEST.json.

Intended use and limits

Training and evaluating translation between African languages. Quality varies a lot by pair: pivot pairs inherit the noise of both English translations, religious_jw text is domain-narrow, synthetic_mt rows are machine translations (capped at 15 % per language pair in the build). No pair is human-verified at sentence level by us.