African-African Parallel Sentences
Collection
Collection of sentence pairs or parallel corpus across African Languages for machine translation.
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703 items
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Updated
Dataset Viewer
score
float32 1.04
1.25
| Pedi
stringlengths 10
495
| Umbundu
stringlengths 10
498
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|---|---|---|
1.249985
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Go Kgotlelela go Fihla Bofelong 129.
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Pandikisa Toke Kesulilo 129.
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1.249599
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Monna le mosadi ba swanetše go swarana bjang?
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Ulume lukãi va sukila oku li tata ndati pokati?
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1.249478
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Nkane batswadi ba ka ba sa ntumelele go dira se?'" - Anne.
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Momo lie olonjali viange ka vi ngecelela oku linga ovina viaco.'" - Anne
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1.249441
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Re tseba bjang gore barongwa ba na le taba le batho?
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Tua kũlĩha ndati okuti ovangelo va kapako omanu?
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1.249441
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Gopola bahlanka ba gago, Abrahama le Isaka le Jakobo.
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Tu konomuisi ulandu wa pita la Avirahama, la Isake, kuenda Yakoba.
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1.249279
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"Ke nna senkgwa sa bophelo.
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"Ame ndimbolo yomuenyo.
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1.249149
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"Ditaba tše tše dibotse tša Mmušo di tla bolelwa lefaseng ka moka gore e be bohlatse go ditšhaba tšohle, ke moka bofelo bo tla tla."
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"Olondaka evi viwa Viusoma vi kundilua koluali luosi ha vi lingi uvangi kolofeka viosi, oco esulilo liya noke."
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1.249002
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31Ka gona, ge le eja goba le enwa goba le dira se sengwe, tšohle le di direle go tumiša Modimo.
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31 Oco, nda vu lia, ale vu nyua, pamue vu linga ovina vikuavo, cosi ci lingili ulamba wa Suku.
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1.248996
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Na o kile wa ikwa bjalo ka Kellie goba Rick?
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Anga hẽ wa liyevele ale nda Kellie ale nda Rick?
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1.248667
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i Leza wa bomi, ke wa bafwepo,
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Eye ha Sukuko yava va fa, te yava va kasi lomuenyo.
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1.248544
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Motseng wo go hweditšwe madi a baprofeta, le a badumedi,
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Mbimbiliya nguayo: "Muli ikeye va uanene maninga a vapolofeto na a vakua ku lela, na a vose vaze va va na tsihi ha mavu."
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1.248024
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Ba bantši ba bona ba fihleletše phetho ye: "Ke hweditše therešo!"
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Vamue pokati kavo va popia vati: "Nda sanga ocili!"
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1.247933
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a tswale mora,
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o cita omõla ulume,
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1.24782
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Mo e ka bago batho ba dimilione tše 70 ba bolailwe ke tlala lekgolong la bo-20 la mengwaga.
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Ci soka 70 kolohuluwa viomanu va fa lonjala kocita ca 20.
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1.247641
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Mo e ka bago ka morago ga dikgwedi tše senyane, Jesu o ile a belegwa.
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Noke yolosãi ecea, Yesu wa citiwa.
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1.24763
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Noa e be le monna yo a lokilego.
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Noha wa kala omunu umue uwa.
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1.247538
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36 Ke gona, ge Morwa a le lokolla, ke mo le tlogo ba le lokolotšwe ruri.
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36 Nda Omõla o vu yovola, vu yovoka ocili.
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1.24743
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Bahu ba sekišwa ka tše di ngwadilwego mangwalong, go iwa ka mediro ya bona.
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Kuenje ava "va fa va tetuluiwa lovina via sonehiwa valivulu [aco], okuti lovilinga viavo."
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1.247398
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Lefelo Leo le Bitšwago ka Leina la Gago 93.
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Ocitumãlo ci Tukuiwa Londuko Yove 93.
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1.247365
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Ka go bane mo bababedi goba ba ba raro ba ko panago ka-leina laka, ke na lebona gona moo."
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Momo apa pali vavali pamue vatatu va liongoluila vonduko yange haipo ñasi pokati kavo."
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1.247341
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Selalelo sa Morena 20.
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Ondalelo ya Ñala 20.
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1.247335
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" 'Bona kgoši ya gago e tla go wena!
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Tala, ohamba yoye te uya kuove!
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1.247291
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O itše go bona: "Ka moka le . . . bana ba motho."
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Eye wa vi sapuila hati: "Vosi yene vu vamanji."
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1.247094
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Ga a kgolwe seo a se bonago.
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Eye ka tavele kovina a mola.
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1.246987
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February 2015 | Kamoo o ka Thabelago Mošomo wa Gago
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Kayovo 2015 | Ndomo o Sanjukila Upange Wove
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1.246952
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Tlogela "go Itsomela Dilo tše Dikgolo"
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Ku ka 'Lisandele Ovina Vinene'
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1.246919
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Ke ka Baka la Eng re Tšofala le go hwa?
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Momo lie tu kukila kuenda tu fila?
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1.2468
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Beibele - Ke ka Baka La'ng e le tše Dintši Gakaakaa?
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Momo Lie ku Kasilili Ambimbiliya Alua?
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1.246786
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Beibele - Ke ka Baka La'ng e le tše Dintši Gakaakaa?
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Momo Lie ku Kasilili Ambimbiliya Alua?
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1.246324
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Empa ke bafe batho bao re swanetšego go ba rata.
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Puãi omanu vapi tua sesamela oku sola?
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1.245847
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Noa le Meetsefula a Magolo - Ke Bomang Bao ba Ilego ba Theetša?
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Noha kuenda Etande Linene - Helie wa Yevelela?
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1.245679
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Batho ka moka ba tla be ba ratana.
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Omanu vosi va ka li sola pokati.
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1.245375
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Ka moka ga rena re dira diphošo.
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Vosi yetu tua siata oku lueya.
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1.245285
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Ithute kamoo o ka dirago seo mohlaleng wa Aborahama.
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Li longisa ndomo o pondola oku setukula ongangu ya Avirahama.
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1.24497
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Mmušo wa Modimo ke kholofelo e nnoši ya batho.
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Usoma wa Suku owo lika u ka malako ovitangi viomanu.
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1.244716
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Ga go e a tlago go Tate ge e se ka nna.
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Lomue iya ku Isia, te lame."
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1.244629
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Mpotšeng ditoro tša lena."
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Sapuiliko olonjoyi viene."
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1.244132
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O tsoga bahung.
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Eye wa pinduka kolofa.
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1.243986
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Ga go yo a yago go Tate ge e se ka nna.
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Lomue iya ku Isia, te lame."
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1.24366
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Ge re ehwa, re lefa molato wa dibe tša rena feela.
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Eci tu fa, tu feta onima yi tunda kekandu lietu muẽle.
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1.243348
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Le se sa dira ntlo ya Tate bobapaletšo!"
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Ko ka lingi onjo ya Isiange ocitumãlo cimue colomĩlu!'
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1.243285
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ya rathang ka sona,
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Ndiaye Abdoulaye Penda
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1.243154
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Ke ithuta maleme a mangwe.
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Ame ndi lilongisa alimi akuavo.
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1.243054
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Jehofa o Ile a Mmitša "Mogwera wa ka"
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Yehova wo Tukula Hati, 'Ekamba Liange'
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1.242987
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Kgane ke mang mo go lena yo a ka ikokeletšago bophelo gannyane ka go bo balabalela?
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"Olyelye ou mokati keni, nande a kale e noshisho, ta dulu okuweda ko koule womafiku aye nande oludimbo limwe?"
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1.242779
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Ke tla ba swarela bokgopo bja bona, gomme nka se sa gopola dibe tša bona.
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Momo ndi ka ecela evĩho liavo, kuenda si ka ivaluka vali akandu avo.'" - Yer.
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1.242713
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Ke motho wa pele yoo Beibele e mo hlalosago ka tsela yeo.
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Eye omunu watete wa tukuiwa Vembimbiliya lonjila ndeyi.
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1.24254
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Adama o hwile ge Henoge a na le mengwaga e 308.
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Adama wa fa eci Enoke a kuata 308 kanyamo.
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1.242514
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Kamoo re ka Aparago Semelo se Sefsa le go Dula re se Apere
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Ndomo tu Wala Omunu Wokaliye Kuenda Oku Amamako Oku ci Linga
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1.242482
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Ke ka baka la'ng le nyaka go mpolaya?"
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Momo lie vu sandela oku njipa?"
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1.242409
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Baloki bona e tla ba beng ba lefase, Ba tla dula mo go lona ka mo go sa felego.
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"Olondingesunga vi piñala ofeka, vi tungamo oloneke ka vi pui."
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1.241932
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O be a ntheetša, a mpalela dingwalwa le go rapela le nna.
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Eye wa ndi yevelela, noke wa ndi tangela ovina vimue, kuenda wa likutilila kumosi lame.
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1.241753
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15 Go lebalelwa dibe.
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15 Akandu etu a eceliwa.
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1.24174
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Jesu a mo fetola a re: "Ruri, ke go botša gore lehono o tla ba le nna paradeising."
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Yesu wo kumbulula hati: 'Hu sapuila etaili okuti, oka kala lame vocumbo ceposo.'
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1.241734
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Na go na le o tee wa babuši goba wa Bafarisei yo a dumelago go yena?
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Siti pokati kasongui ale ka va Fariseo lomue wo kolela?
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1.241593
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Modimo o re Bontšhitše Botho bja Gagwe bjo Bogolo ka Ditsela tše Dintši
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Tua Kuatisiwa Lohenda Yapihãla ya Suku Volonjila Vialua
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1.241469
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O be a nepile, ga bjale ke na le bagwera ba bantši!" - Helena wa nywaga e 20.
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Ocili okuti wa kuatele esunga momo cilo ñuete akamba valua." - Helena okuti o kuete 20 kanyamo.
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1.241001
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Nako yeo e ile ya fela ka October 1914.
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Otembo yaco ya sulila kosãi ya Mbalavipembe yunyamo wo 1914.
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1.240722
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Tsogo ya Jesu - Na e Diregile e le ka Kgonthe?
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Epinduko lia Yesu - Anga hẽ Ulandu Waco wa Pita Muẽle Ocili?
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1.240577
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Mmušo wa Modimo - O tla Bolela Eng go Wena?
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Usoma wa Suku - u Lomboloka Nye Kokuove?
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1.240535
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Re rapela Modimo ka leina la Jesu. - Johane 15:16.
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Tua siata oku likutilila vonduko ya Yesu. - Yoano 15:16.
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1.240413
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Motho yo mongwe le yo mongwe o tla be a na le dijo tše dintši.
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Omanu vosi va ka kuata okulia kualua.
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1.240101
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Ke ka baka la'ng re swanetše go ithuta ka barongwa?
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Momo lie tu sukilila oku lilongisa catiamẽla kovangelo?
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1.240012
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'Ditaba tše Dibotse go Ditšhaba Tšohle, Meloko Yohle le Maleme Ohle'
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'Olondaka Viwa Kolofeka Viosi, Kapata Osi, Kuenda Kalimi Osi'
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1.240001
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Ke'ng seo Daniele 2:44 e re botšago sona mabapi le Mmušo wa Modimo?
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Elivulu lia Daniele 2:44 li tu sapuila nye catiamẽla Kusoma wa Suku?
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1.239807
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Na o Fela o Lewa ke Bodutu le go Boifa?
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Anga hẽ, Eteke Limue wa li Yevele Okuti o Kasi Likaliove Kuenda Lusumba?
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1.239496
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Ke hlwela go e akanya letšatši lohle.
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Ndukuaku vi sokolola ño-o eteke liosi.
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1.239378
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Goba na o ikwa go swana le Ed?
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Ale wa kala nda Ed?
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1.239169
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i Leza wa bomi, ke wa bafwepo,
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Oye Kalunga kovanamwenyo, ndele ke fi Kalunga kovafi.
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1.239123
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"Ke be ke ekwa eka nka se bote motho.
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"Nda kuatele ovisimĩlo viokuti si kolela vali komunu la umue.
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1.239058
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Banamedi ba Bane ba Dipere ba Utolotšwe
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Elomboloko Lialume Vakuãla va Endela Kotuvalu
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1.23905
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Ke moka morongwa yo a tšwago legodimong a iponagatša go yena gomme a mo matlafatša.
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'Ungelo wokilu wo tukulukila kuenda wo kolisa.'
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1.238898
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KGAOLO 11 Ke ka Baka la Eng go na le Tlaišego e Kaakaa?
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OCIPAMA 11 Momo Lie ku Kasilili Ohali Yalua?
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1.238553
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(Johane 3:36) Go bolela'ng go bontšha tumelo?
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(Yoano 3:36) Oku lekisa ekolelo ci lomboloka nye?
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1.238447
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Jesu o ile a re'ng go Maria mmagwe?
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Nye Yesu a sapuila inaye Maria?
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1.238336
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Re tla ya nago go batho ba geno."
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Etu tu enda love kepata liove.'
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1.238307
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Moshe a thothomela, a šia le go lebelela.
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Mose wa kuata usumba kuenje wa sitika ocipala caye.
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1.238138
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Tsebang gore ke na le lena matšatši ka moka go fihla bofelong bja tshepedišo ya dilo."
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Ndele tala, Ame ondi li pamwe nanye omafiku aeshe fiyo okexulilo lefimbo lounyuni.'
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1.238061
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Ke bahlahli ba foufetšego.
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Ovo asongui olomeke.
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1.237756
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"Mathomong ge ke be ke bala ka banamedi ba bane ba dipere ke be ke tšhogile.
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"Onjanja yatete eci nda tanga ulandu watiamẽla kotuvalu tukuãla, nda komõha calua.
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1.237516
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Eupša go na le ba bangwe ba lena bao ba sa dumelego."
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Ndele ope na vamwe vomunye ovo inava itavela."
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1.237441
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Ntwa Yeo e Fetošitšego Lefase
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Uyaki wa Pongolola Oluali
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1.237378
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Ke Bomang Bao ba Eteletšego Pele Batho ba Modimo Lehono?
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Helie o Kasi Oku Songuila Afendeli va Suku Koloneke Vilo?
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1.237219
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Ke ka baka la eng lefase e se paradeise gona bjale?
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Momo lie ongongo ka yi kasilili ofeka yelau koloneke vilo?
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1.237191
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Monna le mosadi ba swanetše go godišana le go hlomphana.
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Ulume kumue lukãi waye va sukila oku li sumbila pokati.
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1.237098
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Ga ke sa swanelwa ke go bitšwa morwago; hle, ntshware bjalo ka yo mongwe wa bathwalwa ba gago.'
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Si sesamela oku tukuiwa vali omolove, ndingise ño ndukuopange wove ukuanganyu."
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1.237069
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11 Lena batswadi, fetšang nako e ntši kamoo le ka kgonago ka gona le na le bana ba lena.
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11 Ene alonjali, sokiyi otembo yalua yoku kala lomãla vene.
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1.236933
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Ba tšama ba tiiša dipelo tša barutiwa, ba ba kgothatša ba re ba tielele tumelong, ba re: Mmušong wa Modimo re tsena ka ditlaišego tše ntši.
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Ndele va pameka eemwenyo dovalongwa, ndele ve va kumaida okudiinina eitavelo, tava ti: Mokuya mouhamba waKalunga otu nokupitila moudjuu uhapu."
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1.23688
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ya bona kamehla."Pes.
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Ndukuaku vi sokolola ño-o eteke liosi." - Osa.
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1.236773
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Na o ka Thuša ka Phuthegong ya Geno?
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O Pondola hẽ Oku Kuatisa Ekongelo o Kasi?
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1.236683
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Petro o Ithutile ka Tebalelo go Mong wa Gagwe
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Petulu wa Lilongisa Oku Kala Ukuakuecela la Cime Caye
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1.236442
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Le apare motho e mofsa, e a bopetšwego go etša Modimo go lokeng le kgethegong ya makgonthe.
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Ndele mu shituke vape momhepo yomadiladilo eni, ndele nye mu djale omunhu mupe a shitwa a fe Kalunga omouyuki nomouyapuki woshili."
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1.236283
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Se ke se se diragaletšego Beverly yo a tsopotšwego pejana.
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Eci oco ca pita la Beverly, wa tukuiwa kefetikilo.
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1.236278
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Go feta moo, go tloga kgale go fihla lehono, pono ya Modimo ka dintwa ga se ya fetoga.
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Toke cilo ocisimĩlo ca Suku catiamẽla kuyaki ka ca pongolokele.
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1.236277
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Nagana ka dilo tše di kgahlišago tšeo re ka ithutago tšona go yena!
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Sokolola kovina vi komõhisa eye a ka tu longisa!
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1.236131
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Re Šireletša Dipelo tša Rena 37.
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Tu Lavi Utima Wetu 37.
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1.235954
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Na o badile ka kelohloko ditokollo tša morago bjale tša Morokami?
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Wa luluvalela ciwa kovipama vimue wa tanga kutala wondavululi umue wokaliye?
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1.2356
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Ga ba nyake go dira thato ya Modimo.
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Ovo ka va yongola oku linga ocipango ca Suku.
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1.235465
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5 2016 O ka Hwetša Kae Khomotšo?
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5 2016 Pi o Pondola Oku Sanga Elembeleko?
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1.235342
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KE MPHO efe e kgahlišago kudu yeo o kilego wa e hwetša?
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OMBANJAILE yipi ya velapo wa tambuile ale vomuenyo wove?
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Pedi-Umbundu_Sentence-Pairs Dataset
This dataset contains sentence pairs for African languages along with similarity scores. It can be used for machine translation, sentence alignment, or other natural language processing tasks.
This dataset is based on the NLLBv1 dataset, published on OPUS under an open-source initiative led by META. You can find more information here: OPUS - NLLB-v1
Metadata
- File Name: Pedi-Umbundu_Sentence-Pairs
- Number of Rows: 66472
- Number of Columns: 3
- Columns: score, Pedi, Umbundu
Dataset Description
The dataset contains sentence pairs in African languages with an associated similarity score. Each row consists of three columns:
score: The similarity score between the two sentences (range from 0 to 1).Pedi: The first sentence in the pair (language 1).Umbundu: The second sentence in the pair (language 2).
This dataset is intended for use in training and evaluating machine learning models for tasks like translation, sentence similarity, and cross-lingual transfer learning.
References
Below are papers related to how the data was collected and used in various multilingual and cross-lingual applications:
[1] Holger Schwenk and Matthijs Douze, Learning Joint Multilingual Sentence Representations with Neural Machine Translation, ACL workshop on Representation Learning for NLP, 2017
[2] Holger Schwenk and Xian Li, A Corpus for Multilingual Document Classification in Eight Languages, LREC, pages 3548-3551, 2018.
[3] Holger Schwenk, Filtering and Mining Parallel Data in a Joint Multilingual Space ACL, July 2018
[4] Alexis Conneau, Guillaume Lample, Ruty Rinott, Adina Williams, Samuel R. Bowman, Holger Schwenk and Veselin Stoyanov, XNLI: Cross-lingual Sentence Understanding through Inference, EMNLP, 2018.
[5] Mikel Artetxe and Holger Schwenk, Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings arXiv, Nov 3 2018.
[6] Mikel Artetxe and Holger Schwenk, Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond arXiv, Dec 26 2018.
[7] Holger Schwenk, Vishrav Chaudhary, Shuo Sun, Hongyu Gong and Paco Guzman, WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia arXiv, July 11 2019.
[8] Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB
[9] Paul-Ambroise Duquenne, Hongyu Gong, Holger Schwenk, Multimodal and Multilingual Embeddings for Large-Scale Speech Mining, NeurIPS 2021, pages 15748-15761.
[10] Kevin Heffernan, Onur Celebi, and Holger Schwenk, Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
4.79 MB
Number of rows:
66,472