bigram
stringlengths 3
56
| lang
stringclasses 153
values | lang_id
int64 1
154
| count
int64 1
296k
|
|---|---|---|---|
Pano pali
|
nya
| 1
| 22
|
pali Mulungu
|
nya
| 1
| 48
|
Mulungu wako
|
nya
| 1
| 360
|
wako Israyeli
|
nya
| 1
| 1
|
Israyeli iwo
|
nya
| 1
| 5
|
iwo anafuula
|
nya
| 1
| 8
|
anafuula yemwe
|
nya
| 1
| 1
|
yemwe anakutulutsa
|
nya
| 1
| 1
|
anakutulutsa iwe
|
nya
| 1
| 1
|
iwe kutuluka
|
nya
| 1
| 1
|
kutuluka m
|
nya
| 1
| 208
|
m dziko
|
nya
| 1
| 6,371
|
dziko la
|
nya
| 1
| 3,965
|
la Igupto
|
nya
| 1
| 38
|
Achibwana amalandira
|
nya
| 1
| 1
|
amalandira cholowa
|
nya
| 1
| 2
|
cholowa cha
|
nya
| 1
| 50
|
cha utsiru
|
nya
| 1
| 1
|
utsiru koma
|
nya
| 1
| 4
|
koma ochenjera
|
nya
| 1
| 1
|
ochenjera amavala
|
nya
| 1
| 1
|
amavala nzeru
|
nya
| 1
| 1
|
nzeru ngati
|
nya
| 1
| 22
|
ngati korona
|
nya
| 1
| 5
|
Chikondi sichitha
|
nya
| 1
| 21
|
sichitha nthaŵi
|
nya
| 1
| 17
|
nthaŵi zonse
|
nya
| 1
| 4,863
|
Chilungamo Chilungamo
|
nya
| 1
| 2
|
Chilungamo Ndicho
|
nya
| 1
| 2
|
Ndicho Mudzichitsata
|
nya
| 1
| 1
|
Inu Mulungu
|
nya
| 1
| 99
|
Mulungu Wanga
|
nya
| 1
| 12
|
Wanga Mundikumbukire
|
nya
| 1
| 2
|
Mundikumbukire pa
|
nya
| 1
| 3
|
pa Zabwino
|
nya
| 1
| 3
|
Zabwino Zimene
|
nya
| 1
| 9
|
Zimene Ndinachita
|
nya
| 1
| 2
|
Iye Adzauka
|
nya
| 1
| 1
|
KHAZIKITSANI mtima
|
nya
| 1
| 1
|
mtima pansi
|
nya
| 1
| 144
|
Khalani mwa
|
nya
| 1
| 2
|
mwa Mtendere
|
nya
| 1
| 1
|
Mtendere ndi
|
nya
| 1
| 81
|
ndi Anthu
|
nya
| 1
| 121
|
Anthu Onse
|
nya
| 1
| 120
|
Kukhala ndi
|
nya
| 1
| 625
|
ndi ana
|
nya
| 1
| 3,355
|
ana kukhala
|
nya
| 1
| 41
|
kukhala wachimwemwe
|
nya
| 1
| 77
|
wachimwemwe ndiyeno
|
nya
| 1
| 1
|
ndiyeno kufa
|
nya
| 1
| 2
|
Kukhuta kwa
|
nya
| 1
| 4
|
kwa wolemera
|
nya
| 1
| 15
|
wolemera sikumgonetsa
|
nya
| 1
| 6
|
sikumgonetsa tulo
|
nya
| 1
| 6
|
Kwaniritsani chimwemwe
|
nya
| 1
| 3
|
chimwemwe changa
|
nya
| 1
| 29
|
changa musachite
|
nya
| 1
| 1
|
musachite kanthu
|
nya
| 1
| 6
|
kanthu monga
|
nya
| 1
| 64
|
monga mwa
|
nya
| 1
| 856
|
mwa chotetana
|
nya
| 1
| 26
|
chotetana kapena
|
nya
| 1
| 26
|
kapena monga
|
nya
| 1
| 121
|
mwa ulemerero
|
nya
| 1
| 34
|
ulemerero wopanda
|
nya
| 1
| 33
|
wopanda pake
|
nya
| 1
| 202
|
pake komatu
|
nya
| 1
| 26
|
komatu ndi
|
nya
| 1
| 58
|
ndi kudzichepetsa
|
nya
| 1
| 120
|
kudzichepetsa mtima
|
nya
| 1
| 38
|
mtima yense
|
nya
| 1
| 23
|
yense ayese
|
nya
| 1
| 24
|
ayese anzake
|
nya
| 1
| 22
|
anzake omposa
|
nya
| 1
| 15
|
omposa iye
|
nya
| 1
| 15
|
iye mwini
|
nya
| 1
| 484
|
mwini munthu
|
nya
| 1
| 5
|
munthu yense
|
nya
| 1
| 147
|
yense asapenyerere
|
nya
| 1
| 18
|
asapenyerere zake
|
nya
| 1
| 23
|
zake za
|
nya
| 1
| 531
|
za iye
|
nya
| 1
| 611
|
iye yekha
|
nya
| 1
| 523
|
yekha koma
|
nya
| 1
| 91
|
koma yense
|
nya
| 1
| 43
|
yense apenyererenso
|
nya
| 1
| 24
|
apenyererenso za
|
nya
| 1
| 25
|
za mnzake
|
nya
| 1
| 89
|
MWACHITA ZOPUSA
|
nya
| 1
| 1
|
Mboni za
|
nya
| 1
| 12,825
|
za Yehova
|
nya
| 1
| 14,508
|
Yehova Zandichinjiriza
|
nya
| 1
| 1
|
Mulungu Ali
|
nya
| 1
| 65
|
Ali Wamkulu
|
nya
| 1
| 4
|
Wamkulu Woposa
|
nya
| 1
| 55
|
Woposa Mitima
|
nya
| 1
| 2
|
Mitima Yathu
|
nya
| 1
| 10
|
Mwandidzoza mutu
|
nya
| 1
| 2
|
mutu wanga
|
nya
| 1
| 30
|
Afri-Bigrams
This dataset contains a large-scale collection of word bigrams extracted from text across 154 African languages. It is meticulously designed to support general research and analysis of African languages, providing foundational data based on two-word sequences.
Background
This dataset provides foundational linguistic data, specifically word bigram frequencies, for African languages. This type of structured data is crucial for various computational linguistic tasks, allowing researchers to explore lexical co-occurrence patterns across 154 languages.
Approach Overview
The dataset exclusively includes word bigrams (sequences of two words).
The data provides the raw frequency counts of these word bigrams for each language. Word bigrams are valuable for analyzing lexical co-occurrence and capturing basic syntactic patterns within the corpus used for extraction.
Dataset Structure
Each row in the dataset represents one word bigram and its frequency for a specific language.
| Column | Description |
|---|---|
| bigram | Extracted sequence (word pair). |
| count | Frequency of the bigram within that language. |
| lang | Two-letter language code. |
| lang_id | Numeric identifier for the language. |
Use Cases
- Statistical analysis of word co-occurrence across African languages.
- Development of language models and embedding techniques.
- Linguistic pattern analysis focusing on common lexical sequences.
- Supporting general multilingual NLP research.
Languages
The dataset covers the following languages. Note that representation may vary across languages.
Acholi (ach), Dangme (ada), Afrikaans (afr), Akan (aka), Alur (alz), Amharic (amh), Algerian Arabic (arq), Moroccan Arabic (ary), Egyptian Arabic (arz), Bamanankan (bam), Basaa (bas), Baoulé (bci), Bemba (bem), Edo (bin), Bulu (bum), Bilen (byn), Chopi (cce), Chuwabu (chw), Chokwe (cjk), Coptic (cop), Seychelles French Creole (crs), Southwestern Dinka (dik), Dinka (din), Zarma (dje), Lukpa (dop), Duala (dua), Jula (dyu), Efik (efi), Éwé (ewe), Fon (fon), Pulaar (fuc), Fulah (ful), Nigerian Fulfulde (fuv), Ga (gaa), Gun (guw), Hausa (hau), Herero (her), Igbo (ibo), Esan (ish), Isoko (iso), Kabyle (kab), Kamba (kam), Kanuri (kau), Kabiyè (kbp), Kabuverdianu (kea), Gikuyu (kik), Kinyarwanda (kin), Kimbundu (kmb), Kongo (kon), Konzo (koo), Kaonde (kqn), Krio (kri), Kisi, Southern (kss), Oshiwambo (kua), Kwangali (kwn), Kikongo (kwy), Lamba (lam), Lingala (lin), Lozi (loz), Luba-Kasai (lua), Luba-Katanga (lub), Luvale (lue), Ganda (lug), Lunda (lun), Dholuo (luo), Mende (men), Morisyen (mfe), Mambwe-Lungu (mgr), Malagasy (mlg), Moore (mos), Mozambican Sign Language (mzy), Min Nan Chinese (nan), Nyemba (nba), Ndau (ndc), Ndonga (ndo), Lomwe (ngl), Northern Sotho (nso), Chichewa (nya), Nyaneka (nyk), Nyankore (nyn), Nyungwe (nyu), Nzema (nzi), Okpe (oke), Oromo (orm), Nigerian Pidgin (pcm), Merina Malagasy (plt), Tarifit (rif), Ruund (rnd), Rundi (run), Sango (sag), Sena (seh), South African Sign Language (sfs), Tachelhit (shi), Sidaama (sid), Shona (sna), Somali (som), Songe (sop), Swati (ssw), Swahili (swa), Congo Swahili (swc), Swahili (swh), Tigrigna (tir), Tiv (tiv), Tetela (tll), Tamashek (tmh), Tonga (tog), Tonga (toh), Tonga (toi), Tswa (tsc), Setswana (tsn), Tsonga (tso), Tooro (ttj), Tumbuka (tum), Umbundu (umb), Urhobo (urh), Venda (ven), Makhuwa (vmw), Wolaytta (wal), Cameroon Pidgin (wes), Wolof (wol), Xhosa (xho), Yao (yao), Yoruba (yor), Zimbabwe Sign Language (zib), Zande (zne), Zambian Sign Language (zsl), Zulu (zul)
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