| --- |
| language: |
| - multilingual |
| license: apache-2.0 |
| tags: |
| - bitext-mining |
| - sentence-embeddings |
| - mteb |
| - multilingual |
| task_categories: |
| - sentence-similarity |
| pretty_name: MTEB BitextMining Aggregated Dataset (Full) |
| size_categories: |
| - 100K<n<1M |
| configs: |
| - config_name: BUCC_v2 |
| data_files: |
| - split: fr_en |
| path: BUCC_v2/fr_en-* |
| - split: ru_en |
| path: BUCC_v2/ru_en-* |
| - split: de_en |
| path: BUCC_v2/de_en-* |
| - split: zh_en |
| path: BUCC_v2/zh_en-* |
| - config_name: BornholmBitextMining |
| data_files: |
| - split: default |
| path: BornholmBitextMining/default-* |
| - config_name: DiaBlaBitextMining |
| data_files: |
| - split: en_fr |
| path: DiaBlaBitextMining/en_fr-* |
| - split: fr_en |
| path: DiaBlaBitextMining/fr_en-* |
| - config_name: IN22GenBitextMining |
| data_files: |
| - split: asm_Beng_ben_Beng |
| path: IN22GenBitextMining/asm_Beng_ben_Beng-* |
| - split: asm_Beng_brx_Deva |
| path: IN22GenBitextMining/asm_Beng_brx_Deva-* |
| - split: asm_Beng_doi_Deva |
| path: IN22GenBitextMining/asm_Beng_doi_Deva-* |
| - split: asm_Beng_eng_Latn |
| path: IN22GenBitextMining/asm_Beng_eng_Latn-* |
| - split: asm_Beng_gom_Deva |
| path: IN22GenBitextMining/asm_Beng_gom_Deva-* |
| - split: asm_Beng_guj_Gujr |
| path: IN22GenBitextMining/asm_Beng_guj_Gujr-* |
| - split: asm_Beng_hin_Deva |
| path: IN22GenBitextMining/asm_Beng_hin_Deva-* |
| - split: asm_Beng_kan_Knda |
| path: IN22GenBitextMining/asm_Beng_kan_Knda-* |
| - split: asm_Beng_kas_Arab |
| path: IN22GenBitextMining/asm_Beng_kas_Arab-* |
| - split: asm_Beng_mai_Deva |
| path: IN22GenBitextMining/asm_Beng_mai_Deva-* |
| - split: asm_Beng_mal_Mlym |
| path: IN22GenBitextMining/asm_Beng_mal_Mlym-* |
| - split: asm_Beng_mar_Deva |
| path: IN22GenBitextMining/asm_Beng_mar_Deva-* |
| - split: asm_Beng_mni_Mtei |
| path: IN22GenBitextMining/asm_Beng_mni_Mtei-* |
| - split: asm_Beng_npi_Deva |
| path: IN22GenBitextMining/asm_Beng_npi_Deva-* |
| - split: asm_Beng_ory_Orya |
| path: IN22GenBitextMining/asm_Beng_ory_Orya-* |
| - split: asm_Beng_pan_Guru |
| path: IN22GenBitextMining/asm_Beng_pan_Guru-* |
| - split: asm_Beng_san_Deva |
| path: IN22GenBitextMining/asm_Beng_san_Deva-* |
| - split: asm_Beng_sat_Olck |
| path: IN22GenBitextMining/asm_Beng_sat_Olck-* |
| - split: asm_Beng_snd_Deva |
| path: IN22GenBitextMining/asm_Beng_snd_Deva-* |
| - split: asm_Beng_tam_Taml |
| path: IN22GenBitextMining/asm_Beng_tam_Taml-* |
| - split: asm_Beng_tel_Telu |
| path: IN22GenBitextMining/asm_Beng_tel_Telu-* |
| - split: asm_Beng_urd_Arab |
| path: IN22GenBitextMining/asm_Beng_urd_Arab-* |
| - split: ben_Beng_asm_Beng |
| path: IN22GenBitextMining/ben_Beng_asm_Beng-* |
| - split: ben_Beng_brx_Deva |
| path: IN22GenBitextMining/ben_Beng_brx_Deva-* |
| - split: ben_Beng_doi_Deva |
| path: IN22GenBitextMining/ben_Beng_doi_Deva-* |
| - split: ben_Beng_eng_Latn |
| path: IN22GenBitextMining/ben_Beng_eng_Latn-* |
| - split: ben_Beng_gom_Deva |
| path: IN22GenBitextMining/ben_Beng_gom_Deva-* |
| - split: ben_Beng_guj_Gujr |
| path: IN22GenBitextMining/ben_Beng_guj_Gujr-* |
| - split: ben_Beng_hin_Deva |
| path: IN22GenBitextMining/ben_Beng_hin_Deva-* |
| - split: ben_Beng_kan_Knda |
| path: IN22GenBitextMining/ben_Beng_kan_Knda-* |
| - split: ben_Beng_kas_Arab |
| path: IN22GenBitextMining/ben_Beng_kas_Arab-* |
| - split: ben_Beng_mai_Deva |
| path: IN22GenBitextMining/ben_Beng_mai_Deva-* |
| - split: ben_Beng_mal_Mlym |
| path: IN22GenBitextMining/ben_Beng_mal_Mlym-* |
| - split: ben_Beng_mar_Deva |
| path: IN22GenBitextMining/ben_Beng_mar_Deva-* |
| - split: ben_Beng_mni_Mtei |
| path: IN22GenBitextMining/ben_Beng_mni_Mtei-* |
| - split: ben_Beng_npi_Deva |
| path: IN22GenBitextMining/ben_Beng_npi_Deva-* |
| - split: ben_Beng_ory_Orya |
| path: IN22GenBitextMining/ben_Beng_ory_Orya-* |
| - split: ben_Beng_pan_Guru |
| path: IN22GenBitextMining/ben_Beng_pan_Guru-* |
| - split: ben_Beng_san_Deva |
| path: IN22GenBitextMining/ben_Beng_san_Deva-* |
| - split: ben_Beng_sat_Olck |
| path: IN22GenBitextMining/ben_Beng_sat_Olck-* |
| - split: ben_Beng_snd_Deva |
| path: IN22GenBitextMining/ben_Beng_snd_Deva-* |
| - split: ben_Beng_tam_Taml |
| path: IN22GenBitextMining/ben_Beng_tam_Taml-* |
| - split: ben_Beng_tel_Telu |
| path: IN22GenBitextMining/ben_Beng_tel_Telu-* |
| - split: ben_Beng_urd_Arab |
| path: IN22GenBitextMining/ben_Beng_urd_Arab-* |
| - split: brx_Deva_asm_Beng |
| path: IN22GenBitextMining/brx_Deva_asm_Beng-* |
| - split: brx_Deva_ben_Beng |
| path: IN22GenBitextMining/brx_Deva_ben_Beng-* |
| - split: brx_Deva_doi_Deva |
| path: IN22GenBitextMining/brx_Deva_doi_Deva-* |
| - split: brx_Deva_eng_Latn |
| path: IN22GenBitextMining/brx_Deva_eng_Latn-* |
| - split: brx_Deva_gom_Deva |
| path: IN22GenBitextMining/brx_Deva_gom_Deva-* |
| - split: brx_Deva_guj_Gujr |
| path: IN22GenBitextMining/brx_Deva_guj_Gujr-* |
| - split: brx_Deva_hin_Deva |
| path: IN22GenBitextMining/brx_Deva_hin_Deva-* |
| - split: brx_Deva_kan_Knda |
| path: IN22GenBitextMining/brx_Deva_kan_Knda-* |
| - split: brx_Deva_kas_Arab |
| path: IN22GenBitextMining/brx_Deva_kas_Arab-* |
| - split: brx_Deva_mai_Deva |
| path: IN22GenBitextMining/brx_Deva_mai_Deva-* |
| - split: brx_Deva_mal_Mlym |
| path: IN22GenBitextMining/brx_Deva_mal_Mlym-* |
| - split: brx_Deva_mar_Deva |
| path: IN22GenBitextMining/brx_Deva_mar_Deva-* |
| - split: brx_Deva_mni_Mtei |
| path: IN22GenBitextMining/brx_Deva_mni_Mtei-* |
| - split: brx_Deva_npi_Deva |
| path: IN22GenBitextMining/brx_Deva_npi_Deva-* |
| - split: brx_Deva_ory_Orya |
| path: IN22GenBitextMining/brx_Deva_ory_Orya-* |
| - split: brx_Deva_pan_Guru |
| path: IN22GenBitextMining/brx_Deva_pan_Guru-* |
| - split: brx_Deva_san_Deva |
| path: IN22GenBitextMining/brx_Deva_san_Deva-* |
| - split: brx_Deva_sat_Olck |
| path: IN22GenBitextMining/brx_Deva_sat_Olck-* |
| - split: brx_Deva_snd_Deva |
| path: IN22GenBitextMining/brx_Deva_snd_Deva-* |
| - split: brx_Deva_tam_Taml |
| path: IN22GenBitextMining/brx_Deva_tam_Taml-* |
| - split: brx_Deva_tel_Telu |
| path: IN22GenBitextMining/brx_Deva_tel_Telu-* |
| - split: brx_Deva_urd_Arab |
| path: IN22GenBitextMining/brx_Deva_urd_Arab-* |
| - split: doi_Deva_asm_Beng |
| path: IN22GenBitextMining/doi_Deva_asm_Beng-* |
| - split: doi_Deva_ben_Beng |
| path: IN22GenBitextMining/doi_Deva_ben_Beng-* |
| - split: doi_Deva_brx_Deva |
| path: IN22GenBitextMining/doi_Deva_brx_Deva-* |
| - split: doi_Deva_eng_Latn |
| path: IN22GenBitextMining/doi_Deva_eng_Latn-* |
| - split: doi_Deva_gom_Deva |
| path: IN22GenBitextMining/doi_Deva_gom_Deva-* |
| - split: doi_Deva_guj_Gujr |
| path: IN22GenBitextMining/doi_Deva_guj_Gujr-* |
| - split: doi_Deva_hin_Deva |
| path: IN22GenBitextMining/doi_Deva_hin_Deva-* |
| - split: doi_Deva_kan_Knda |
| path: IN22GenBitextMining/doi_Deva_kan_Knda-* |
| - split: doi_Deva_kas_Arab |
| path: IN22GenBitextMining/doi_Deva_kas_Arab-* |
| - split: doi_Deva_mai_Deva |
| path: IN22GenBitextMining/doi_Deva_mai_Deva-* |
| - split: doi_Deva_mal_Mlym |
| path: IN22GenBitextMining/doi_Deva_mal_Mlym-* |
| - split: doi_Deva_mar_Deva |
| path: IN22GenBitextMining/doi_Deva_mar_Deva-* |
| - split: doi_Deva_mni_Mtei |
| path: IN22GenBitextMining/doi_Deva_mni_Mtei-* |
| - split: doi_Deva_npi_Deva |
| path: IN22GenBitextMining/doi_Deva_npi_Deva-* |
| - split: doi_Deva_ory_Orya |
| path: IN22GenBitextMining/doi_Deva_ory_Orya-* |
| - split: doi_Deva_pan_Guru |
| path: IN22GenBitextMining/doi_Deva_pan_Guru-* |
| - split: doi_Deva_san_Deva |
| path: IN22GenBitextMining/doi_Deva_san_Deva-* |
| - split: doi_Deva_sat_Olck |
| path: IN22GenBitextMining/doi_Deva_sat_Olck-* |
| - split: doi_Deva_snd_Deva |
| path: IN22GenBitextMining/doi_Deva_snd_Deva-* |
| - split: doi_Deva_tam_Taml |
| path: IN22GenBitextMining/doi_Deva_tam_Taml-* |
| - split: doi_Deva_tel_Telu |
| path: IN22GenBitextMining/doi_Deva_tel_Telu-* |
| - split: doi_Deva_urd_Arab |
| path: IN22GenBitextMining/doi_Deva_urd_Arab-* |
| - split: eng_Latn_asm_Beng |
| path: IN22GenBitextMining/eng_Latn_asm_Beng-* |
| - split: eng_Latn_ben_Beng |
| path: IN22GenBitextMining/eng_Latn_ben_Beng-* |
| - split: eng_Latn_brx_Deva |
| path: IN22GenBitextMining/eng_Latn_brx_Deva-* |
| - split: eng_Latn_doi_Deva |
| path: IN22GenBitextMining/eng_Latn_doi_Deva-* |
| - split: eng_Latn_gom_Deva |
| path: IN22GenBitextMining/eng_Latn_gom_Deva-* |
| - split: eng_Latn_guj_Gujr |
| path: IN22GenBitextMining/eng_Latn_guj_Gujr-* |
| - split: eng_Latn_hin_Deva |
| path: IN22GenBitextMining/eng_Latn_hin_Deva-* |
| - split: eng_Latn_kan_Knda |
| path: IN22GenBitextMining/eng_Latn_kan_Knda-* |
| - split: eng_Latn_kas_Arab |
| path: IN22GenBitextMining/eng_Latn_kas_Arab-* |
| - split: eng_Latn_mai_Deva |
| path: IN22GenBitextMining/eng_Latn_mai_Deva-* |
| - split: eng_Latn_mal_Mlym |
| path: IN22GenBitextMining/eng_Latn_mal_Mlym-* |
| - split: eng_Latn_mar_Deva |
| path: IN22GenBitextMining/eng_Latn_mar_Deva-* |
| - split: eng_Latn_mni_Mtei |
| path: IN22GenBitextMining/eng_Latn_mni_Mtei-* |
| - split: eng_Latn_npi_Deva |
| path: IN22GenBitextMining/eng_Latn_npi_Deva-* |
| - split: eng_Latn_ory_Orya |
| path: IN22GenBitextMining/eng_Latn_ory_Orya-* |
| - split: eng_Latn_pan_Guru |
| path: IN22GenBitextMining/eng_Latn_pan_Guru-* |
| - split: eng_Latn_san_Deva |
| path: IN22GenBitextMining/eng_Latn_san_Deva-* |
| - split: eng_Latn_sat_Olck |
| path: IN22GenBitextMining/eng_Latn_sat_Olck-* |
| - split: eng_Latn_snd_Deva |
| path: IN22GenBitextMining/eng_Latn_snd_Deva-* |
| - split: eng_Latn_tam_Taml |
| path: IN22GenBitextMining/eng_Latn_tam_Taml-* |
| - split: eng_Latn_tel_Telu |
| path: IN22GenBitextMining/eng_Latn_tel_Telu-* |
| - split: eng_Latn_urd_Arab |
| path: IN22GenBitextMining/eng_Latn_urd_Arab-* |
| - split: gom_Deva_asm_Beng |
| path: IN22GenBitextMining/gom_Deva_asm_Beng-* |
| - split: gom_Deva_ben_Beng |
| path: IN22GenBitextMining/gom_Deva_ben_Beng-* |
| - split: gom_Deva_brx_Deva |
| path: IN22GenBitextMining/gom_Deva_brx_Deva-* |
| - split: gom_Deva_doi_Deva |
| path: IN22GenBitextMining/gom_Deva_doi_Deva-* |
| - split: gom_Deva_eng_Latn |
| path: IN22GenBitextMining/gom_Deva_eng_Latn-* |
| - split: gom_Deva_guj_Gujr |
| path: IN22GenBitextMining/gom_Deva_guj_Gujr-* |
| - split: gom_Deva_hin_Deva |
| path: IN22GenBitextMining/gom_Deva_hin_Deva-* |
| - split: gom_Deva_kan_Knda |
| path: IN22GenBitextMining/gom_Deva_kan_Knda-* |
| - split: gom_Deva_kas_Arab |
| path: IN22GenBitextMining/gom_Deva_kas_Arab-* |
| - split: gom_Deva_mai_Deva |
| path: IN22GenBitextMining/gom_Deva_mai_Deva-* |
| - split: gom_Deva_mal_Mlym |
| path: IN22GenBitextMining/gom_Deva_mal_Mlym-* |
| - split: gom_Deva_mar_Deva |
| path: IN22GenBitextMining/gom_Deva_mar_Deva-* |
| - split: gom_Deva_mni_Mtei |
| path: IN22GenBitextMining/gom_Deva_mni_Mtei-* |
| - split: gom_Deva_npi_Deva |
| path: IN22GenBitextMining/gom_Deva_npi_Deva-* |
| - split: gom_Deva_ory_Orya |
| path: IN22GenBitextMining/gom_Deva_ory_Orya-* |
| - split: gom_Deva_pan_Guru |
| path: IN22GenBitextMining/gom_Deva_pan_Guru-* |
| - split: gom_Deva_san_Deva |
| path: IN22GenBitextMining/gom_Deva_san_Deva-* |
| - split: gom_Deva_sat_Olck |
| path: IN22GenBitextMining/gom_Deva_sat_Olck-* |
| - config_name: IndicGenBenchFloresBitextMining |
| data_files: |
| - split: asm_eng |
| path: IndicGenBenchFloresBitextMining/asm_eng-* |
| - split: awa_eng |
| path: IndicGenBenchFloresBitextMining/awa_eng-* |
| - split: ben_eng |
| path: IndicGenBenchFloresBitextMining/ben_eng-* |
| - split: bgc_eng |
| path: IndicGenBenchFloresBitextMining/bgc_eng-* |
| - split: bho_eng |
| path: IndicGenBenchFloresBitextMining/bho_eng-* |
| - split: bod_eng |
| path: IndicGenBenchFloresBitextMining/bod_eng-* |
| - split: boy_eng |
| path: IndicGenBenchFloresBitextMining/boy_eng-* |
| - split: eng_asm |
| path: IndicGenBenchFloresBitextMining/eng_asm-* |
| - split: eng_awa |
| path: IndicGenBenchFloresBitextMining/eng_awa-* |
| - split: eng_ben |
| path: IndicGenBenchFloresBitextMining/eng_ben-* |
| - split: eng_bgc |
| path: IndicGenBenchFloresBitextMining/eng_bgc-* |
| - split: eng_bho |
| path: IndicGenBenchFloresBitextMining/eng_bho-* |
| - split: eng_bod |
| path: IndicGenBenchFloresBitextMining/eng_bod-* |
| - split: eng_boy |
| path: IndicGenBenchFloresBitextMining/eng_boy-* |
| - split: eng_gbm |
| path: IndicGenBenchFloresBitextMining/eng_gbm-* |
| - split: eng_gom |
| path: IndicGenBenchFloresBitextMining/eng_gom-* |
| - split: eng_guj |
| path: IndicGenBenchFloresBitextMining/eng_guj-* |
| - split: eng_hin |
| path: IndicGenBenchFloresBitextMining/eng_hin-* |
| - split: eng_hne |
| path: IndicGenBenchFloresBitextMining/eng_hne-* |
| - split: eng_kan |
| path: IndicGenBenchFloresBitextMining/eng_kan-* |
| - split: eng_mai |
| path: IndicGenBenchFloresBitextMining/eng_mai-* |
| - split: eng_mal |
| path: IndicGenBenchFloresBitextMining/eng_mal-* |
| - split: eng_mar |
| path: IndicGenBenchFloresBitextMining/eng_mar-* |
| - split: eng_mni |
| path: IndicGenBenchFloresBitextMining/eng_mni-* |
| - split: eng_mup |
| path: IndicGenBenchFloresBitextMining/eng_mup-* |
| - split: eng_mwr |
| path: IndicGenBenchFloresBitextMining/eng_mwr-* |
| - split: eng_nep |
| path: IndicGenBenchFloresBitextMining/eng_nep-* |
| - split: eng_ory |
| path: IndicGenBenchFloresBitextMining/eng_ory-* |
| - split: eng_pan |
| path: IndicGenBenchFloresBitextMining/eng_pan-* |
| - split: eng_pus |
| path: IndicGenBenchFloresBitextMining/eng_pus-* |
| - split: eng_raj |
| path: IndicGenBenchFloresBitextMining/eng_raj-* |
| - split: eng_san |
| path: IndicGenBenchFloresBitextMining/eng_san-* |
| - split: eng_sat |
| path: IndicGenBenchFloresBitextMining/eng_sat-* |
| - split: eng_tam |
| path: IndicGenBenchFloresBitextMining/eng_tam-* |
| - split: eng_tel |
| path: IndicGenBenchFloresBitextMining/eng_tel-* |
| - split: eng_urd |
| path: IndicGenBenchFloresBitextMining/eng_urd-* |
| - split: gbm_eng |
| path: IndicGenBenchFloresBitextMining/gbm_eng-* |
| - split: gom_eng |
| path: IndicGenBenchFloresBitextMining/gom_eng-* |
| - split: guj_eng |
| path: IndicGenBenchFloresBitextMining/guj_eng-* |
| - split: hin_eng |
| path: IndicGenBenchFloresBitextMining/hin_eng-* |
| - split: hne_eng |
| path: IndicGenBenchFloresBitextMining/hne_eng-* |
| - split: kan_eng |
| path: IndicGenBenchFloresBitextMining/kan_eng-* |
| - split: mai_eng |
| path: IndicGenBenchFloresBitextMining/mai_eng-* |
| - split: mal_eng |
| path: IndicGenBenchFloresBitextMining/mal_eng-* |
| - split: mar_eng |
| path: IndicGenBenchFloresBitextMining/mar_eng-* |
| - split: mni_eng |
| path: IndicGenBenchFloresBitextMining/mni_eng-* |
| - split: mup_eng |
| path: IndicGenBenchFloresBitextMining/mup_eng-* |
| - split: mwr_eng |
| path: IndicGenBenchFloresBitextMining/mwr_eng-* |
| - split: nep_eng |
| path: IndicGenBenchFloresBitextMining/nep_eng-* |
| - split: ory_eng |
| path: IndicGenBenchFloresBitextMining/ory_eng-* |
| - split: pan_eng |
| path: IndicGenBenchFloresBitextMining/pan_eng-* |
| - split: pus_eng |
| path: IndicGenBenchFloresBitextMining/pus_eng-* |
| - split: raj_eng |
| path: IndicGenBenchFloresBitextMining/raj_eng-* |
| - split: san_eng |
| path: IndicGenBenchFloresBitextMining/san_eng-* |
| - split: sat_eng |
| path: IndicGenBenchFloresBitextMining/sat_eng-* |
| - split: tam_eng |
| path: IndicGenBenchFloresBitextMining/tam_eng-* |
| - split: tel_eng |
| path: IndicGenBenchFloresBitextMining/tel_eng-* |
| - split: urd_eng |
| path: IndicGenBenchFloresBitextMining/urd_eng-* |
| - config_name: NollySentiBitextMining |
| data_files: |
| - split: en_ha |
| path: NollySentiBitextMining/en_ha-* |
| - split: en_ig |
| path: NollySentiBitextMining/en_ig-* |
| - split: en_pcm |
| path: NollySentiBitextMining/en_pcm-* |
| - split: en_yo |
| path: NollySentiBitextMining/en_yo-* |
| - config_name: NorwegianCourtsBitextMining |
| data_files: |
| - split: default |
| path: NorwegianCourtsBitextMining/default-* |
| - config_name: NusaTranslationBitextMining |
| data_files: |
| - split: ind_abs |
| path: NusaTranslationBitextMining/ind_abs-* |
| - split: ind_bew |
| path: NusaTranslationBitextMining/ind_bew-* |
| - split: ind_bhp |
| path: NusaTranslationBitextMining/ind_bhp-* |
| - split: ind_btk |
| path: NusaTranslationBitextMining/ind_btk-* |
| - split: ind_jav |
| path: NusaTranslationBitextMining/ind_jav-* |
| - split: ind_mad |
| path: NusaTranslationBitextMining/ind_mad-* |
| - split: ind_mak |
| path: NusaTranslationBitextMining/ind_mak-* |
| - split: ind_min |
| path: NusaTranslationBitextMining/ind_min-* |
| - split: ind_mui |
| path: NusaTranslationBitextMining/ind_mui-* |
| - split: ind_rej |
| path: NusaTranslationBitextMining/ind_rej-* |
| - split: ind_sun |
| path: NusaTranslationBitextMining/ind_sun-* |
| - config_name: NusaXBitextMining |
| data_files: |
| - split: eng_ace |
| path: NusaXBitextMining/eng_ace-* |
| - split: eng_ban |
| path: NusaXBitextMining/eng_ban-* |
| - split: eng_bbc |
| path: NusaXBitextMining/eng_bbc-* |
| - split: eng_bjn |
| path: NusaXBitextMining/eng_bjn-* |
| - split: eng_bug |
| path: NusaXBitextMining/eng_bug-* |
| - split: eng_ind |
| path: NusaXBitextMining/eng_ind-* |
| - split: eng_jav |
| path: NusaXBitextMining/eng_jav-* |
| - split: eng_mad |
| path: NusaXBitextMining/eng_mad-* |
| - split: eng_min |
| path: NusaXBitextMining/eng_min-* |
| - split: eng_nij |
| path: NusaXBitextMining/eng_nij-* |
| - split: eng_sun |
| path: NusaXBitextMining/eng_sun-* |
| - config_name: Tatoeba |
| data_files: |
| - split: sqi_eng |
| path: Tatoeba/sqi_eng-* |
| - split: fry_eng |
| path: Tatoeba/fry_eng-* |
| - split: kur_eng |
| path: Tatoeba/kur_eng-* |
| - split: tur_eng |
| path: Tatoeba/tur_eng-* |
| - split: deu_eng |
| path: Tatoeba/deu_eng-* |
| - split: nld_eng |
| path: Tatoeba/nld_eng-* |
| - split: ron_eng |
| path: Tatoeba/ron_eng-* |
| - split: ang_eng |
| path: Tatoeba/ang_eng-* |
| - split: ido_eng |
| path: Tatoeba/ido_eng-* |
| - split: jav_eng |
| path: Tatoeba/jav_eng-* |
| - split: isl_eng |
| path: Tatoeba/isl_eng-* |
| - split: slv_eng |
| path: Tatoeba/slv_eng-* |
| - split: cym_eng |
| path: Tatoeba/cym_eng-* |
| - split: kaz_eng |
| path: Tatoeba/kaz_eng-* |
| - split: est_eng |
| path: Tatoeba/est_eng-* |
| - split: heb_eng |
| path: Tatoeba/heb_eng-* |
| - split: gla_eng |
| path: Tatoeba/gla_eng-* |
| - split: mar_eng |
| path: Tatoeba/mar_eng-* |
| - split: lat_eng |
| path: Tatoeba/lat_eng-* |
| - split: bel_eng |
| path: Tatoeba/bel_eng-* |
| - split: pms_eng |
| path: Tatoeba/pms_eng-* |
| - split: gle_eng |
| path: Tatoeba/gle_eng-* |
| - split: pes_eng |
| path: Tatoeba/pes_eng-* |
| - split: nob_eng |
| path: Tatoeba/nob_eng-* |
| - split: bul_eng |
| path: Tatoeba/bul_eng-* |
| - split: cbk_eng |
| path: Tatoeba/cbk_eng-* |
| - split: hun_eng |
| path: Tatoeba/hun_eng-* |
| - split: uig_eng |
| path: Tatoeba/uig_eng-* |
| - split: rus_eng |
| path: Tatoeba/rus_eng-* |
| - split: spa_eng |
| path: Tatoeba/spa_eng-* |
| - split: hye_eng |
| path: Tatoeba/hye_eng-* |
| - split: tel_eng |
| path: Tatoeba/tel_eng-* |
| - split: afr_eng |
| path: Tatoeba/afr_eng-* |
| - split: mon_eng |
| path: Tatoeba/mon_eng-* |
| - split: arz_eng |
| path: Tatoeba/arz_eng-* |
| - split: hrv_eng |
| path: Tatoeba/hrv_eng-* |
| - split: nov_eng |
| path: Tatoeba/nov_eng-* |
| - split: gsw_eng |
| path: Tatoeba/gsw_eng-* |
| - split: nds_eng |
| path: Tatoeba/nds_eng-* |
| - split: ukr_eng |
| path: Tatoeba/ukr_eng-* |
| - split: uzb_eng |
| path: Tatoeba/uzb_eng-* |
| - split: lit_eng |
| path: Tatoeba/lit_eng-* |
| - split: ina_eng |
| path: Tatoeba/ina_eng-* |
| - split: lfn_eng |
| path: Tatoeba/lfn_eng-* |
| - split: zsm_eng |
| path: Tatoeba/zsm_eng-* |
| - split: ita_eng |
| path: Tatoeba/ita_eng-* |
| - split: cmn_eng |
| path: Tatoeba/cmn_eng-* |
| - split: lvs_eng |
| path: Tatoeba/lvs_eng-* |
| - split: glg_eng |
| path: Tatoeba/glg_eng-* |
| - split: ceb_eng |
| path: Tatoeba/ceb_eng-* |
| - split: bre_eng |
| path: Tatoeba/bre_eng-* |
| - split: ben_eng |
| path: Tatoeba/ben_eng-* |
| - split: swg_eng |
| path: Tatoeba/swg_eng-* |
| - split: arq_eng |
| path: Tatoeba/arq_eng-* |
| - split: kab_eng |
| path: Tatoeba/kab_eng-* |
| - split: fra_eng |
| path: Tatoeba/fra_eng-* |
| - split: por_eng |
| path: Tatoeba/por_eng-* |
| - split: tat_eng |
| path: Tatoeba/tat_eng-* |
| - split: oci_eng |
| path: Tatoeba/oci_eng-* |
| - split: pol_eng |
| path: Tatoeba/pol_eng-* |
| - split: war_eng |
| path: Tatoeba/war_eng-* |
| - split: aze_eng |
| path: Tatoeba/aze_eng-* |
| - split: vie_eng |
| path: Tatoeba/vie_eng-* |
| - split: nno_eng |
| path: Tatoeba/nno_eng-* |
| - split: cha_eng |
| path: Tatoeba/cha_eng-* |
| - split: mhr_eng |
| path: Tatoeba/mhr_eng-* |
| - split: dan_eng |
| path: Tatoeba/dan_eng-* |
| - split: ell_eng |
| path: Tatoeba/ell_eng-* |
| - split: amh_eng |
| path: Tatoeba/amh_eng-* |
| - split: pam_eng |
| path: Tatoeba/pam_eng-* |
| - split: hsb_eng |
| path: Tatoeba/hsb_eng-* |
| - split: srp_eng |
| path: Tatoeba/srp_eng-* |
| - split: epo_eng |
| path: Tatoeba/epo_eng-* |
| - split: kzj_eng |
| path: Tatoeba/kzj_eng-* |
| - split: awa_eng |
| path: Tatoeba/awa_eng-* |
| - split: fao_eng |
| path: Tatoeba/fao_eng-* |
| - split: mal_eng |
| path: Tatoeba/mal_eng-* |
| - split: ile_eng |
| path: Tatoeba/ile_eng-* |
| - split: bos_eng |
| path: Tatoeba/bos_eng-* |
| - split: cor_eng |
| path: Tatoeba/cor_eng-* |
| - split: cat_eng |
| path: Tatoeba/cat_eng-* |
| - split: eus_eng |
| path: Tatoeba/eus_eng-* |
| - split: yue_eng |
| path: Tatoeba/yue_eng-* |
| - split: swe_eng |
| path: Tatoeba/swe_eng-* |
| - split: dtp_eng |
| path: Tatoeba/dtp_eng-* |
| - split: kat_eng |
| path: Tatoeba/kat_eng-* |
| - split: jpn_eng |
| path: Tatoeba/jpn_eng-* |
| - split: csb_eng |
| path: Tatoeba/csb_eng-* |
| - split: xho_eng |
| path: Tatoeba/xho_eng-* |
| - split: orv_eng |
| path: Tatoeba/orv_eng-* |
| - split: ind_eng |
| path: Tatoeba/ind_eng-* |
| - split: tuk_eng |
| path: Tatoeba/tuk_eng-* |
| - split: max_eng |
| path: Tatoeba/max_eng-* |
| - split: swh_eng |
| path: Tatoeba/swh_eng-* |
| - split: hin_eng |
| path: Tatoeba/hin_eng-* |
| - split: dsb_eng |
| path: Tatoeba/dsb_eng-* |
| - split: ber_eng |
| path: Tatoeba/ber_eng-* |
| - split: tam_eng |
| path: Tatoeba/tam_eng-* |
| - split: slk_eng |
| path: Tatoeba/slk_eng-* |
| - split: tgl_eng |
| path: Tatoeba/tgl_eng-* |
| - split: ast_eng |
| path: Tatoeba/ast_eng-* |
| - split: mkd_eng |
| path: Tatoeba/mkd_eng-* |
| - split: khm_eng |
| path: Tatoeba/khm_eng-* |
| - split: ces_eng |
| path: Tatoeba/ces_eng-* |
| - split: tzl_eng |
| path: Tatoeba/tzl_eng-* |
| - split: urd_eng |
| path: Tatoeba/urd_eng-* |
| - split: ara_eng |
| path: Tatoeba/ara_eng-* |
| - split: kor_eng |
| path: Tatoeba/kor_eng-* |
| - split: yid_eng |
| path: Tatoeba/yid_eng-* |
| - split: fin_eng |
| path: Tatoeba/fin_eng-* |
| - split: tha_eng |
| path: Tatoeba/tha_eng-* |
| - split: wuu_eng |
| path: Tatoeba/wuu_eng-* |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| dataset_info: |
| - config_name: BUCC_v2 |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: fr_en |
| num_bytes: 2127711 |
| num_examples: 9086 |
| - name: ru_en |
| num_bytes: 4713530 |
| num_examples: 14435 |
| - name: de_en |
| num_bytes: 2373378 |
| num_examples: 9580 |
| - name: zh_en |
| num_bytes: 425398 |
| num_examples: 1899 |
| download_size: 4995323 |
| dataset_size: 9640017 |
| - config_name: BornholmBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: default |
| num_bytes: 905545 |
| num_examples: 6785 |
| download_size: 331753 |
| dataset_size: 905545 |
| - config_name: DiaBlaBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: en_fr |
| num_bytes: 843941 |
| num_examples: 5748 |
| - name: fr_en |
| num_bytes: 843941 |
| num_examples: 5748 |
| download_size: 725286 |
| dataset_size: 1687882 |
| - config_name: IN22GenBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: asm_Beng_ben_Beng |
| num_bytes: 915680 |
| num_examples: 1024 |
| - name: asm_Beng_brx_Deva |
| num_bytes: 949101 |
| num_examples: 1024 |
| - name: asm_Beng_doi_Deva |
| num_bytes: 921310 |
| num_examples: 1024 |
| - name: asm_Beng_eng_Latn |
| num_bytes: 672370 |
| num_examples: 1024 |
| - name: asm_Beng_gom_Deva |
| num_bytes: 915888 |
| num_examples: 1024 |
| - name: asm_Beng_guj_Gujr |
| num_bytes: 905828 |
| num_examples: 1024 |
| - name: asm_Beng_hin_Deva |
| num_bytes: 924168 |
| num_examples: 1024 |
| - name: asm_Beng_kan_Knda |
| num_bytes: 982934 |
| num_examples: 1024 |
| - name: asm_Beng_kas_Arab |
| num_bytes: 807167 |
| num_examples: 1024 |
| - name: asm_Beng_mai_Deva |
| num_bytes: 904788 |
| num_examples: 1024 |
| - name: asm_Beng_mal_Mlym |
| num_bytes: 1019092 |
| num_examples: 1024 |
| - name: asm_Beng_mar_Deva |
| num_bytes: 945191 |
| num_examples: 1024 |
| - name: asm_Beng_mni_Mtei |
| num_bytes: 920032 |
| num_examples: 1024 |
| - name: asm_Beng_npi_Deva |
| num_bytes: 925943 |
| num_examples: 1024 |
| - name: asm_Beng_ory_Orya |
| num_bytes: 978870 |
| num_examples: 1024 |
| - name: asm_Beng_pan_Guru |
| num_bytes: 883929 |
| num_examples: 1024 |
| - name: asm_Beng_san_Deva |
| num_bytes: 942149 |
| num_examples: 1024 |
| - name: asm_Beng_sat_Olck |
| num_bytes: 955884 |
| num_examples: 1024 |
| - name: asm_Beng_snd_Deva |
| num_bytes: 924307 |
| num_examples: 1024 |
| - name: asm_Beng_tam_Taml |
| num_bytes: 1026680 |
| num_examples: 1024 |
| - name: asm_Beng_tel_Telu |
| num_bytes: 938937 |
| num_examples: 1024 |
| - name: asm_Beng_urd_Arab |
| num_bytes: 788703 |
| num_examples: 1024 |
| - name: ben_Beng_asm_Beng |
| num_bytes: 915680 |
| num_examples: 1024 |
| - name: ben_Beng_brx_Deva |
| num_bytes: 922319 |
| num_examples: 1024 |
| - name: ben_Beng_doi_Deva |
| num_bytes: 894528 |
| num_examples: 1024 |
| - name: ben_Beng_eng_Latn |
| num_bytes: 645588 |
| num_examples: 1024 |
| - name: ben_Beng_gom_Deva |
| num_bytes: 889106 |
| num_examples: 1024 |
| - name: ben_Beng_guj_Gujr |
| num_bytes: 879046 |
| num_examples: 1024 |
| - name: ben_Beng_hin_Deva |
| num_bytes: 897386 |
| num_examples: 1024 |
| - name: ben_Beng_kan_Knda |
| num_bytes: 956152 |
| num_examples: 1024 |
| - name: ben_Beng_kas_Arab |
| num_bytes: 780385 |
| num_examples: 1024 |
| - name: ben_Beng_mai_Deva |
| num_bytes: 878006 |
| num_examples: 1024 |
| - name: ben_Beng_mal_Mlym |
| num_bytes: 992310 |
| num_examples: 1024 |
| - name: ben_Beng_mar_Deva |
| num_bytes: 918409 |
| num_examples: 1024 |
| - name: ben_Beng_mni_Mtei |
| num_bytes: 893250 |
| num_examples: 1024 |
| - name: ben_Beng_npi_Deva |
| num_bytes: 899161 |
| num_examples: 1024 |
| - name: ben_Beng_ory_Orya |
| num_bytes: 952088 |
| num_examples: 1024 |
| - name: ben_Beng_pan_Guru |
| num_bytes: 857147 |
| num_examples: 1024 |
| - name: ben_Beng_san_Deva |
| num_bytes: 915367 |
| num_examples: 1024 |
| - name: ben_Beng_sat_Olck |
| num_bytes: 929102 |
| num_examples: 1024 |
| - name: ben_Beng_snd_Deva |
| num_bytes: 897525 |
| num_examples: 1024 |
| - name: ben_Beng_tam_Taml |
| num_bytes: 999898 |
| num_examples: 1024 |
| - name: ben_Beng_tel_Telu |
| num_bytes: 912155 |
| num_examples: 1024 |
| - name: ben_Beng_urd_Arab |
| num_bytes: 761921 |
| num_examples: 1024 |
| - name: brx_Deva_asm_Beng |
| num_bytes: 949101 |
| num_examples: 1024 |
| - name: brx_Deva_ben_Beng |
| num_bytes: 922319 |
| num_examples: 1024 |
| - name: brx_Deva_doi_Deva |
| num_bytes: 927949 |
| num_examples: 1024 |
| - name: brx_Deva_eng_Latn |
| num_bytes: 679009 |
| num_examples: 1024 |
| - name: brx_Deva_gom_Deva |
| num_bytes: 922527 |
| num_examples: 1024 |
| - name: brx_Deva_guj_Gujr |
| num_bytes: 912467 |
| num_examples: 1024 |
| - name: brx_Deva_hin_Deva |
| num_bytes: 930807 |
| num_examples: 1024 |
| - name: brx_Deva_kan_Knda |
| num_bytes: 989573 |
| num_examples: 1024 |
| - name: brx_Deva_kas_Arab |
| num_bytes: 813806 |
| num_examples: 1024 |
| - name: brx_Deva_mai_Deva |
| num_bytes: 911427 |
| num_examples: 1024 |
| - name: brx_Deva_mal_Mlym |
| num_bytes: 1025731 |
| num_examples: 1024 |
| - name: brx_Deva_mar_Deva |
| num_bytes: 951830 |
| num_examples: 1024 |
| - name: brx_Deva_mni_Mtei |
| num_bytes: 926671 |
| num_examples: 1024 |
| - name: brx_Deva_npi_Deva |
| num_bytes: 932582 |
| num_examples: 1024 |
| - name: brx_Deva_ory_Orya |
| num_bytes: 985509 |
| num_examples: 1024 |
| - name: brx_Deva_pan_Guru |
| num_bytes: 890568 |
| num_examples: 1024 |
| - name: brx_Deva_san_Deva |
| num_bytes: 948788 |
| num_examples: 1024 |
| - name: brx_Deva_sat_Olck |
| num_bytes: 962523 |
| num_examples: 1024 |
| - name: brx_Deva_snd_Deva |
| num_bytes: 930946 |
| num_examples: 1024 |
| - name: brx_Deva_tam_Taml |
| num_bytes: 1033319 |
| num_examples: 1024 |
| - name: brx_Deva_tel_Telu |
| num_bytes: 945576 |
| num_examples: 1024 |
| - name: brx_Deva_urd_Arab |
| num_bytes: 795342 |
| num_examples: 1024 |
| - name: doi_Deva_asm_Beng |
| num_bytes: 921310 |
| num_examples: 1024 |
| - name: doi_Deva_ben_Beng |
| num_bytes: 894528 |
| num_examples: 1024 |
| - name: doi_Deva_brx_Deva |
| num_bytes: 927949 |
| num_examples: 1024 |
| - name: doi_Deva_eng_Latn |
| num_bytes: 651218 |
| num_examples: 1024 |
| - name: doi_Deva_gom_Deva |
| num_bytes: 894736 |
| num_examples: 1024 |
| - name: doi_Deva_guj_Gujr |
| num_bytes: 884676 |
| num_examples: 1024 |
| - name: doi_Deva_hin_Deva |
| num_bytes: 903016 |
| num_examples: 1024 |
| - name: doi_Deva_kan_Knda |
| num_bytes: 961782 |
| num_examples: 1024 |
| - name: doi_Deva_kas_Arab |
| num_bytes: 786015 |
| num_examples: 1024 |
| - name: doi_Deva_mai_Deva |
| num_bytes: 883636 |
| num_examples: 1024 |
| - name: doi_Deva_mal_Mlym |
| num_bytes: 997940 |
| num_examples: 1024 |
| - name: doi_Deva_mar_Deva |
| num_bytes: 924039 |
| num_examples: 1024 |
| - name: doi_Deva_mni_Mtei |
| num_bytes: 898880 |
| num_examples: 1024 |
| - name: doi_Deva_npi_Deva |
| num_bytes: 904791 |
| num_examples: 1024 |
| - name: doi_Deva_ory_Orya |
| num_bytes: 957718 |
| num_examples: 1024 |
| - name: doi_Deva_pan_Guru |
| num_bytes: 862777 |
| num_examples: 1024 |
| - name: doi_Deva_san_Deva |
| num_bytes: 920997 |
| num_examples: 1024 |
| - name: doi_Deva_sat_Olck |
| num_bytes: 934732 |
| num_examples: 1024 |
| - name: doi_Deva_snd_Deva |
| num_bytes: 903155 |
| num_examples: 1024 |
| - name: doi_Deva_tam_Taml |
| num_bytes: 1005528 |
| num_examples: 1024 |
| - name: doi_Deva_tel_Telu |
| num_bytes: 917785 |
| num_examples: 1024 |
| - name: doi_Deva_urd_Arab |
| num_bytes: 767551 |
| num_examples: 1024 |
| - name: eng_Latn_asm_Beng |
| num_bytes: 672370 |
| num_examples: 1024 |
| - name: eng_Latn_ben_Beng |
| num_bytes: 645588 |
| num_examples: 1024 |
| - name: eng_Latn_brx_Deva |
| num_bytes: 679009 |
| num_examples: 1024 |
| - name: eng_Latn_doi_Deva |
| num_bytes: 651218 |
| num_examples: 1024 |
| - name: eng_Latn_gom_Deva |
| num_bytes: 645796 |
| num_examples: 1024 |
| - name: eng_Latn_guj_Gujr |
| num_bytes: 635736 |
| num_examples: 1024 |
| - name: eng_Latn_hin_Deva |
| num_bytes: 654076 |
| num_examples: 1024 |
| - name: eng_Latn_kan_Knda |
| num_bytes: 712842 |
| num_examples: 1024 |
| - name: eng_Latn_kas_Arab |
| num_bytes: 537075 |
| num_examples: 1024 |
| - name: eng_Latn_mai_Deva |
| num_bytes: 634696 |
| num_examples: 1024 |
| - name: eng_Latn_mal_Mlym |
| num_bytes: 749000 |
| num_examples: 1024 |
| - name: eng_Latn_mar_Deva |
| num_bytes: 675099 |
| num_examples: 1024 |
| - name: eng_Latn_mni_Mtei |
| num_bytes: 649940 |
| num_examples: 1024 |
| - name: eng_Latn_npi_Deva |
| num_bytes: 655851 |
| num_examples: 1024 |
| - name: eng_Latn_ory_Orya |
| num_bytes: 708778 |
| num_examples: 1024 |
| - name: eng_Latn_pan_Guru |
| num_bytes: 613837 |
| num_examples: 1024 |
| - name: eng_Latn_san_Deva |
| num_bytes: 672057 |
| num_examples: 1024 |
| - name: eng_Latn_sat_Olck |
| num_bytes: 685792 |
| num_examples: 1024 |
| - name: eng_Latn_snd_Deva |
| num_bytes: 654215 |
| num_examples: 1024 |
| - name: eng_Latn_tam_Taml |
| num_bytes: 756588 |
| num_examples: 1024 |
| - name: eng_Latn_tel_Telu |
| num_bytes: 668845 |
| num_examples: 1024 |
| - name: eng_Latn_urd_Arab |
| num_bytes: 518611 |
| num_examples: 1024 |
| - name: gom_Deva_asm_Beng |
| num_bytes: 915888 |
| num_examples: 1024 |
| - name: gom_Deva_ben_Beng |
| num_bytes: 889106 |
| num_examples: 1024 |
| - name: gom_Deva_brx_Deva |
| num_bytes: 922527 |
| num_examples: 1024 |
| - name: gom_Deva_doi_Deva |
| num_bytes: 894736 |
| num_examples: 1024 |
| - name: gom_Deva_eng_Latn |
| num_bytes: 645796 |
| num_examples: 1024 |
| - name: gom_Deva_guj_Gujr |
| num_bytes: 879254 |
| num_examples: 1024 |
| - name: gom_Deva_hin_Deva |
| num_bytes: 897594 |
| num_examples: 1024 |
| - name: gom_Deva_kan_Knda |
| num_bytes: 956360 |
| num_examples: 1024 |
| - name: gom_Deva_kas_Arab |
| num_bytes: 780593 |
| num_examples: 1024 |
| - name: gom_Deva_mai_Deva |
| num_bytes: 878214 |
| num_examples: 1024 |
| - name: gom_Deva_mal_Mlym |
| num_bytes: 992518 |
| num_examples: 1024 |
| - name: gom_Deva_mar_Deva |
| num_bytes: 918617 |
| num_examples: 1024 |
| - name: gom_Deva_mni_Mtei |
| num_bytes: 893458 |
| num_examples: 1024 |
| - name: gom_Deva_npi_Deva |
| num_bytes: 899369 |
| num_examples: 1024 |
| - name: gom_Deva_ory_Orya |
| num_bytes: 952296 |
| num_examples: 1024 |
| - name: gom_Deva_pan_Guru |
| num_bytes: 857355 |
| num_examples: 1024 |
| - name: gom_Deva_san_Deva |
| num_bytes: 915575 |
| num_examples: 1024 |
| - name: gom_Deva_sat_Olck |
| num_bytes: 929310 |
| num_examples: 1024 |
| download_size: 43694888 |
| dataset_size: 110224194 |
| - config_name: IndicGenBenchFloresBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: asm_eng |
| num_bytes: 1056946 |
| num_examples: 2009 |
| - name: awa_eng |
| num_bytes: 1048599 |
| num_examples: 2009 |
| - name: ben_eng |
| num_bytes: 1074234 |
| num_examples: 2009 |
| - name: bgc_eng |
| num_bytes: 1036830 |
| num_examples: 2009 |
| - name: bho_eng |
| num_bytes: 1040988 |
| num_examples: 2009 |
| - name: bod_eng |
| num_bytes: 1257640 |
| num_examples: 2009 |
| - name: boy_eng |
| num_bytes: 1161403 |
| num_examples: 2009 |
| - name: eng_asm |
| num_bytes: 1056968 |
| num_examples: 2009 |
| - name: eng_awa |
| num_bytes: 1048493 |
| num_examples: 2009 |
| - name: eng_ben |
| num_bytes: 1074234 |
| num_examples: 2009 |
| - name: eng_bgc |
| num_bytes: 1036830 |
| num_examples: 2009 |
| - name: eng_bho |
| num_bytes: 1041035 |
| num_examples: 2009 |
| - name: eng_bod |
| num_bytes: 1257558 |
| num_examples: 2009 |
| - name: eng_boy |
| num_bytes: 1161403 |
| num_examples: 2009 |
| - name: eng_gbm |
| num_bytes: 1050717 |
| num_examples: 2009 |
| - name: eng_gom |
| num_bytes: 1056819 |
| num_examples: 2009 |
| - name: eng_guj |
| num_bytes: 1045771 |
| num_examples: 2009 |
| - name: eng_hin |
| num_bytes: 1059315 |
| num_examples: 2009 |
| - name: eng_hne |
| num_bytes: 1038653 |
| num_examples: 2009 |
| - name: eng_kan |
| num_bytes: 1132860 |
| num_examples: 2009 |
| - name: eng_mai |
| num_bytes: 1055548 |
| num_examples: 2009 |
| - name: eng_mal |
| num_bytes: 1203090 |
| num_examples: 2009 |
| - name: eng_mar |
| num_bytes: 1091179 |
| num_examples: 2009 |
| - name: eng_mni |
| num_bytes: 1117401 |
| num_examples: 2009 |
| - name: eng_mup |
| num_bytes: 1058706 |
| num_examples: 2009 |
| - name: eng_mwr |
| num_bytes: 1062446 |
| num_examples: 2009 |
| - name: eng_nep |
| num_bytes: 1062632 |
| num_examples: 2009 |
| - name: eng_ory |
| num_bytes: 1107245 |
| num_examples: 2009 |
| - name: eng_pan |
| num_bytes: 1070204 |
| num_examples: 2009 |
| - name: eng_pus |
| num_bytes: 828135 |
| num_examples: 2009 |
| - name: eng_raj |
| num_bytes: 1058173 |
| num_examples: 2009 |
| - name: eng_san |
| num_bytes: 1080078 |
| num_examples: 2009 |
| - name: eng_sat |
| num_bytes: 1123190 |
| num_examples: 2009 |
| - name: eng_tam |
| num_bytes: 1220422 |
| num_examples: 2009 |
| - name: eng_tel |
| num_bytes: 1092493 |
| num_examples: 2009 |
| - name: eng_urd |
| num_bytes: 853498 |
| num_examples: 2009 |
| - name: gbm_eng |
| num_bytes: 1050717 |
| num_examples: 2009 |
| - name: gom_eng |
| num_bytes: 1056819 |
| num_examples: 2009 |
| - name: guj_eng |
| num_bytes: 1045771 |
| num_examples: 2009 |
| - name: hin_eng |
| num_bytes: 1059335 |
| num_examples: 2009 |
| - name: hne_eng |
| num_bytes: 1038672 |
| num_examples: 2009 |
| - name: kan_eng |
| num_bytes: 1133075 |
| num_examples: 2009 |
| - name: mai_eng |
| num_bytes: 1055542 |
| num_examples: 2009 |
| - name: mal_eng |
| num_bytes: 1203089 |
| num_examples: 2009 |
| - name: mar_eng |
| num_bytes: 1091578 |
| num_examples: 2009 |
| - name: mni_eng |
| num_bytes: 1117396 |
| num_examples: 2009 |
| - name: mup_eng |
| num_bytes: 1058706 |
| num_examples: 2009 |
| - name: mwr_eng |
| num_bytes: 1062446 |
| num_examples: 2009 |
| - name: nep_eng |
| num_bytes: 1062632 |
| num_examples: 2009 |
| - name: ory_eng |
| num_bytes: 1107245 |
| num_examples: 2009 |
| - name: pan_eng |
| num_bytes: 1070205 |
| num_examples: 2009 |
| - name: pus_eng |
| num_bytes: 828136 |
| num_examples: 2009 |
| - name: raj_eng |
| num_bytes: 1058173 |
| num_examples: 2009 |
| - name: san_eng |
| num_bytes: 1080358 |
| num_examples: 2009 |
| - name: sat_eng |
| num_bytes: 1123190 |
| num_examples: 2009 |
| - name: tam_eng |
| num_bytes: 1220422 |
| num_examples: 2009 |
| - name: tel_eng |
| num_bytes: 1092511 |
| num_examples: 2009 |
| - name: urd_eng |
| num_bytes: 853499 |
| num_examples: 2009 |
| download_size: 27552478 |
| dataset_size: 62291253 |
| - config_name: NollySentiBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: en_ha |
| num_bytes: 141324 |
| num_examples: 410 |
| - name: en_ig |
| num_bytes: 142407 |
| num_examples: 410 |
| - name: en_pcm |
| num_bytes: 135981 |
| num_examples: 410 |
| - name: en_yo |
| num_bytes: 157241 |
| num_examples: 410 |
| download_size: 310379 |
| dataset_size: 576953 |
| - config_name: NorwegianCourtsBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: default |
| num_bytes: 265698 |
| num_examples: 1137 |
| download_size: 116989 |
| dataset_size: 265698 |
| - config_name: NusaTranslationBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: ind_abs |
| num_bytes: 365680 |
| num_examples: 1000 |
| - name: ind_bew |
| num_bytes: 2420537 |
| num_examples: 6600 |
| - name: ind_bhp |
| num_bytes: 331696 |
| num_examples: 1000 |
| - name: ind_btk |
| num_bytes: 2389908 |
| num_examples: 6600 |
| - name: ind_jav |
| num_bytes: 2384271 |
| num_examples: 6600 |
| - name: ind_mad |
| num_bytes: 2435301 |
| num_examples: 6600 |
| - name: ind_mak |
| num_bytes: 2423126 |
| num_examples: 6600 |
| - name: ind_min |
| num_bytes: 2399033 |
| num_examples: 6600 |
| - name: ind_mui |
| num_bytes: 371449 |
| num_examples: 1000 |
| - name: ind_rej |
| num_bytes: 368437 |
| num_examples: 1000 |
| - name: ind_sun |
| num_bytes: 2418407 |
| num_examples: 6600 |
| download_size: 10574540 |
| dataset_size: 18307845 |
| - config_name: NusaXBitextMining |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: eng_ace |
| num_bytes: 184722 |
| num_examples: 500 |
| - name: eng_ban |
| num_bytes: 187380 |
| num_examples: 500 |
| - name: eng_bbc |
| num_bytes: 189184 |
| num_examples: 500 |
| - name: eng_bjn |
| num_bytes: 187328 |
| num_examples: 500 |
| - name: eng_bug |
| num_bytes: 191552 |
| num_examples: 500 |
| - name: eng_ind |
| num_bytes: 187480 |
| num_examples: 500 |
| - name: eng_jav |
| num_bytes: 185271 |
| num_examples: 500 |
| - name: eng_mad |
| num_bytes: 187942 |
| num_examples: 500 |
| - name: eng_min |
| num_bytes: 184912 |
| num_examples: 500 |
| - name: eng_nij |
| num_bytes: 185800 |
| num_examples: 500 |
| - name: eng_sun |
| num_bytes: 187025 |
| num_examples: 500 |
| download_size: 1164585 |
| dataset_size: 2058596 |
| - config_name: Tatoeba |
| features: |
| - name: sentence1 |
| dtype: string |
| - name: sentence2 |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: source_dataset |
| dtype: string |
| - name: original_split |
| dtype: string |
| - name: config |
| dtype: string |
| splits: |
| - name: sqi_eng |
| num_bytes: 122146 |
| num_examples: 1000 |
| - name: fry_eng |
| num_bytes: 20712 |
| num_examples: 173 |
| - name: kur_eng |
| num_bytes: 45667 |
| num_examples: 410 |
| - name: tur_eng |
| num_bytes: 120885 |
| num_examples: 1000 |
| - name: deu_eng |
| num_bytes: 154567 |
| num_examples: 1000 |
| - name: nld_eng |
| num_bytes: 122263 |
| num_examples: 1000 |
| - name: ron_eng |
| num_bytes: 121484 |
| num_examples: 1000 |
| - name: ang_eng |
| num_bytes: 21746 |
| num_examples: 134 |
| - name: ido_eng |
| num_bytes: 114933 |
| num_examples: 1000 |
| - name: jav_eng |
| num_bytes: 23958 |
| num_examples: 205 |
| - name: isl_eng |
| num_bytes: 128821 |
| num_examples: 1000 |
| - name: slv_eng |
| num_bytes: 93523 |
| num_examples: 823 |
| - name: cym_eng |
| num_bytes: 60754 |
| num_examples: 575 |
| - name: kaz_eng |
| num_bytes: 75353 |
| num_examples: 575 |
| - name: est_eng |
| num_bytes: 108728 |
| num_examples: 1000 |
| - name: heb_eng |
| num_bytes: 132500 |
| num_examples: 1000 |
| - name: gla_eng |
| num_bytes: 96048 |
| num_examples: 829 |
| - name: mar_eng |
| num_bytes: 149542 |
| num_examples: 1000 |
| - name: lat_eng |
| num_bytes: 118854 |
| num_examples: 1000 |
| - name: bel_eng |
| num_bytes: 146932 |
| num_examples: 1000 |
| - name: pms_eng |
| num_bytes: 64255 |
| num_examples: 525 |
| - name: gle_eng |
| num_bytes: 107423 |
| num_examples: 1000 |
| - name: pes_eng |
| num_bytes: 142719 |
| num_examples: 1000 |
| - name: nob_eng |
| num_bytes: 117481 |
| num_examples: 1000 |
| - name: bul_eng |
| num_bytes: 151279 |
| num_examples: 1000 |
| - name: cbk_eng |
| num_bytes: 111726 |
| num_examples: 1000 |
| - name: hun_eng |
| num_bytes: 117889 |
| num_examples: 1000 |
| - name: uig_eng |
| num_bytes: 139052 |
| num_examples: 1000 |
| - name: rus_eng |
| num_bytes: 141472 |
| num_examples: 1000 |
| - name: spa_eng |
| num_bytes: 121266 |
| num_examples: 1000 |
| - name: hye_eng |
| num_bytes: 105044 |
| num_examples: 742 |
| - name: tel_eng |
| num_bytes: 36609 |
| num_examples: 234 |
| - name: afr_eng |
| num_bytes: 108635 |
| num_examples: 1000 |
| - name: mon_eng |
| num_bytes: 66088 |
| num_examples: 440 |
| - name: arz_eng |
| num_bytes: 54851 |
| num_examples: 477 |
| - name: hrv_eng |
| num_bytes: 113934 |
| num_examples: 1000 |
| - name: nov_eng |
| num_bytes: 26309 |
| num_examples: 257 |
| - name: gsw_eng |
| num_bytes: 10438 |
| num_examples: 117 |
| - name: nds_eng |
| num_bytes: 112458 |
| num_examples: 1000 |
| - name: ukr_eng |
| num_bytes: 130931 |
| num_examples: 1000 |
| - name: uzb_eng |
| num_bytes: 45744 |
| num_examples: 428 |
| - name: lit_eng |
| num_bytes: 114243 |
| num_examples: 1000 |
| - name: ina_eng |
| num_bytes: 136502 |
| num_examples: 1000 |
| - name: lfn_eng |
| num_bytes: 120490 |
| num_examples: 1000 |
| - name: zsm_eng |
| num_bytes: 128209 |
| num_examples: 1000 |
| - name: ita_eng |
| num_bytes: 114833 |
| num_examples: 1000 |
| - name: cmn_eng |
| num_bytes: 117931 |
| num_examples: 1000 |
| - name: lvs_eng |
| num_bytes: 112206 |
| num_examples: 1000 |
| - name: glg_eng |
| num_bytes: 125576 |
| num_examples: 1000 |
| - name: ceb_eng |
| num_bytes: 65538 |
| num_examples: 600 |
| - name: bre_eng |
| num_bytes: 100080 |
| num_examples: 1000 |
| - name: ben_eng |
| num_bytes: 140703 |
| num_examples: 1000 |
| - name: swg_eng |
| num_bytes: 12209 |
| num_examples: 112 |
| - name: arq_eng |
| num_bytes: 122033 |
| num_examples: 911 |
| - name: kab_eng |
| num_bytes: 111726 |
| num_examples: 1000 |
| - name: fra_eng |
| num_bytes: 129018 |
| num_examples: 1000 |
| - name: por_eng |
| num_bytes: 124185 |
| num_examples: 1000 |
| - name: tat_eng |
| num_bytes: 141546 |
| num_examples: 1000 |
| - name: oci_eng |
| num_bytes: 110752 |
| num_examples: 1000 |
| - name: pol_eng |
| num_bytes: 120148 |
| num_examples: 1000 |
| - name: war_eng |
| num_bytes: 120826 |
| num_examples: 1000 |
| - name: aze_eng |
| num_bytes: 108400 |
| num_examples: 1000 |
| - name: vie_eng |
| num_bytes: 140407 |
| num_examples: 1000 |
| - name: nno_eng |
| num_bytes: 117572 |
| num_examples: 1000 |
| - name: cha_eng |
| num_bytes: 17929 |
| num_examples: 137 |
| - name: mhr_eng |
| num_bytes: 134104 |
| num_examples: 1000 |
| - name: dan_eng |
| num_bytes: 119826 |
| num_examples: 1000 |
| - name: ell_eng |
| num_bytes: 127961 |
| num_examples: 1000 |
| - name: amh_eng |
| num_bytes: 18104 |
| num_examples: 168 |
| - name: pam_eng |
| num_bytes: 112464 |
| num_examples: 1000 |
| - name: hsb_eng |
| num_bytes: 52308 |
| num_examples: 483 |
| - name: srp_eng |
| num_bytes: 122115 |
| num_examples: 1000 |
| - name: epo_eng |
| num_bytes: 133841 |
| num_examples: 1000 |
| - name: kzj_eng |
| num_bytes: 122309 |
| num_examples: 1000 |
| - name: awa_eng |
| num_bytes: 27596 |
| num_examples: 231 |
| - name: fao_eng |
| num_bytes: 29226 |
| num_examples: 262 |
| - name: mal_eng |
| num_bytes: 128380 |
| num_examples: 687 |
| - name: ile_eng |
| num_bytes: 99680 |
| num_examples: 1000 |
| - name: bos_eng |
| num_bytes: 35066 |
| num_examples: 354 |
| - name: cor_eng |
| num_bytes: 93849 |
| num_examples: 1000 |
| - name: cat_eng |
| num_bytes: 122815 |
| num_examples: 1000 |
| - name: eus_eng |
| num_bytes: 115068 |
| num_examples: 1000 |
| - name: yue_eng |
| num_bytes: 124086 |
| num_examples: 1000 |
| - name: swe_eng |
| num_bytes: 111248 |
| num_examples: 1000 |
| - name: dtp_eng |
| num_bytes: 114064 |
| num_examples: 1000 |
| - name: kat_eng |
| num_bytes: 108714 |
| num_examples: 746 |
| - name: jpn_eng |
| num_bytes: 142083 |
| num_examples: 1000 |
| - name: csb_eng |
| num_bytes: 29584 |
| num_examples: 253 |
| - name: xho_eng |
| num_bytes: 14385 |
| num_examples: 142 |
| - name: orv_eng |
| num_bytes: 101942 |
| num_examples: 835 |
| - name: ind_eng |
| num_bytes: 123844 |
| num_examples: 1000 |
| - name: tuk_eng |
| num_bytes: 19169 |
| num_examples: 203 |
| - name: max_eng |
| num_bytes: 31590 |
| num_examples: 284 |
| - name: swh_eng |
| num_bytes: 39577 |
| num_examples: 390 |
| - name: hin_eng |
| num_bytes: 171558 |
| num_examples: 1000 |
| - name: dsb_eng |
| num_bytes: 52150 |
| num_examples: 479 |
| - name: ber_eng |
| num_bytes: 112627 |
| num_examples: 1000 |
| - name: tam_eng |
| num_bytes: 54484 |
| num_examples: 307 |
| - name: slk_eng |
| num_bytes: 109760 |
| num_examples: 1000 |
| - name: tgl_eng |
| num_bytes: 117138 |
| num_examples: 1000 |
| - name: ast_eng |
| num_bytes: 15506 |
| num_examples: 127 |
| - name: mkd_eng |
| num_bytes: 132826 |
| num_examples: 1000 |
| - name: khm_eng |
| num_bytes: 109362 |
| num_examples: 722 |
| - name: ces_eng |
| num_bytes: 113396 |
| num_examples: 1000 |
| - name: tzl_eng |
| num_bytes: 9339 |
| num_examples: 104 |
| - name: urd_eng |
| num_bytes: 137712 |
| num_examples: 1000 |
| - name: ara_eng |
| num_bytes: 121650 |
| num_examples: 1000 |
| - name: kor_eng |
| num_bytes: 128139 |
| num_examples: 1000 |
| - name: yid_eng |
| num_bytes: 122356 |
| num_examples: 848 |
| - name: fin_eng |
| num_bytes: 124669 |
| num_examples: 1000 |
| - name: tha_eng |
| num_bytes: 90050 |
| num_examples: 548 |
| - name: wuu_eng |
| num_bytes: 123826 |
| num_examples: 1000 |
| download_size: 5020276 |
| dataset_size: 11059627 |
| --- |
| |
| # MTEB BitextMining Aggregated Dataset (Full) |
|
|
| This dataset aggregates **ALL configs** from 10 BitextMining datasets in the MTEB (Massive Text Embedding Benchmark) Multilingual v2 benchmark into a single, unified dataset for comprehensive bitext mining evaluation. |
|
|
| ## Dataset Summary |
|
|
| - **Total Examples**: 448,229 sentence pairs |
| - **Source Datasets (Configs)**: 10 MTEB BitextMining tasks |
| - **Total Splits**: 332 language pairs/configurations |
| - **Languages**: 300+ unique language codes across all datasets |
| - **Task**: Bitext Mining (parallel sentence retrieval) |
| - **Format**: Standardized schema across all sources |
|
|
| ## Structure |
|
|
| Each **source dataset** is a **config**, and each **original config** (language pair) within that dataset is a **split**. |
|
|
| ### Example Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load specific config (source dataset) |
| tatoeba = load_dataset("SaylorTwift/mteb-bitext-mining-aggregated", "Tatoeba") |
| # This gives you 112 splits, one for each language pair |
| |
| # Access a specific language pair split |
| french_english = tatoeba['fra-eng'] |
| print(f"French-English pairs: {len(french_english)}") |
| |
| # Load another config |
| indic = load_dataset("SaylorTwift/mteb-bitext-mining-aggregated", "IndicGenBenchFloresBitextMining") |
| # This gives you 58 splits for different Indic language pairs |
| |
| # Access a split |
| hindi_english = indic['hin-eng'] |
| ``` |
|
|
| ## Schema |
|
|
| Each example contains: |
| - `sentence1` (string): First sentence of the pair |
| - `sentence2` (string): Second sentence of the pair (translation/parallel text) |
| - `lang` (string): Language pair code (e.g., "fra-eng", "de-en") |
| - `source_dataset` (string): Original MTEB dataset name |
| - `original_split` (string): Original split name (train/validation/test) |
| - `config` (string): Original config name |
|
|
| ## Configs (Source Datasets) |
|
|
| | Config | Splits | Examples | Description | |
| |--------|--------|----------|-------------| |
| | **Tatoeba** | 112 | 88,877 | Tatoeba sentence pairs across 112 language pairs | |
| | **IN22GenBitextMining** | 128 | 131,072 | Indic language pairs (23 languages, all combinations) | |
| | **IndicGenBenchFloresBitextMining** | 58 | 116,522 | Indic languages with English from Flores | |
| | **NusaTranslationBitextMining** | 11 | 50,200 | Indonesian regional language pairs | |
| | **BUCC_v2** | 4 | 35,000 | BUCC bitext mining (de-en, fr-en, ru-en, zh-en) | |
| | **DiaBlaBitextMining** | 2 | 11,496 | English-French dialogue pairs (both directions) | |
| | **BornholmBitextMining** | 1 | 6,785 | Danish dialect pairs | |
| | **NusaXBitextMining** | 11 | 5,500 | Indonesian languages with English | |
| | **NollySentiBitextMining** | 4 | 1,640 | Nigerian languages with English | |
| | **NorwegianCourtsBitextMining** | 1 | 1,137 | Norwegian court document pairs | |
| |
| **Total**: 10 configs, 332 splits, 448,229 examples |
| |
| ## Example Splits by Config |
| |
| ### Tatoeba (112 language pairs) |
| `sqi-eng`, `fry-eng`, `kur-eng`, `tur-eng`, `deu-eng`, `ell-eng`, `spa-eng`, `fra-eng`, `ita-eng`, `jpn-eng`, `cmn-eng`, `kor-eng`, `ara-eng`, `rus-eng`, `por-eng`, `hin-eng`, etc. |
| |
| ### IN22GenBitextMining (128 Indic pairs) |
| `asm_Beng-ben_Beng`, `asm_Beng-eng_Latn`, `ben_Beng-hin_Deva`, `guj_Gujr-mar_Deva`, etc. (all combinations of 23 Indic languages) |
| |
| ### IndicGenBenchFloresBitextMining (58 pairs) |
| `asm-eng`, `awa-eng`, `ben-eng`, `bgc-eng`, `bho-eng`, `bod-eng`, `guj-eng`, `hin-eng`, `kan-eng`, `mal-eng`, `mar-eng`, `nep-eng`, `ory-eng`, `pan-eng`, `tam-eng`, `tel-eng`, `urd-eng`, etc. |
| |
| ### BUCC_v2 (4 language pairs) |
| `de-en`, `fr-en`, `ru-en`, `zh-en` |
| |
| ### NusaTranslationBitextMining (11 Indonesian languages) |
| `ind-abs`, `ind-bew`, `ind-bhp`, `ind-btk`, `ind-jav`, `ind-mad`, `ind-mak`, `ind-min`, `ind-mui`, `ind-rej`, `ind-sun` |
| |
| ### NusaXBitextMining (11 pairs) |
| `eng-ace`, `eng-ban`, `eng-bbc`, `eng-bjn`, `eng-bug`, `eng-ind`, `eng-jav`, `eng-mad`, `eng-min`, `eng-nij`, `eng-sun` |
| |
| ## Usage Examples |
| |
| ### Load all language pairs from a specific source |
| |
| ```python |
| from datasets import load_dataset |
| |
| # Load all Tatoeba language pairs |
| tatoeba = load_dataset("SaylorTwift/mteb-bitext-mining-aggregated", "Tatoeba") |
| |
| # Iterate through all language pairs |
| for lang_pair, dataset in tatoeba.items(): |
| print(f"{lang_pair}: {len(dataset)} pairs") |
| ``` |
| |
| ### Load a specific language pair |
| |
| ```python |
| # Load just German-English from BUCC |
| bucc = load_dataset("SaylorTwift/mteb-bitext-mining-aggregated", "BUCC_v2") |
| de_en = bucc['de-en'] |
| |
| for example in de_en: |
| print(f"DE: {example['sentence1']}") |
| print(f"EN: {example['sentence2']}") |
| print() |
| ``` |
| |
| ### Filter by language across all datasets |
| |
| ```python |
| # Load Tatoeba |
| tatoeba = load_dataset("SaylorTwift/mteb-bitext-mining-aggregated", "Tatoeba") |
| |
| # Get all examples for a specific language pair |
| french_english = tatoeba['fra-eng'] |
| print(f"Found {len(french_english)} French-English pairs") |
| ``` |
| |
| ## Excluded Datasets |
| |
| **BibleNLPBitextMining** (828 configs, 900+ languages) was excluded due to incompatible schema that uses language codes as column names instead of the standard `sentence1`/`sentence2` format. |
| |
| **FloresBitextMining** and **NTREXBitextMining** were excluded in the previous version but may be revisitable with updated processing. |
| |
| ## Citation |
| |
| If you use this dataset, please cite the MTEB benchmark: |
| |
| ```bibtex |
| @article{muennighoff2022mteb, |
| title={MTEB: Massive Text Embedding Benchmark}, |
| author={Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo{\"\i}c and Reimers, Nils}, |
| journal={arXiv preprint arXiv:2210.07316}, |
| year={2022} |
| } |
| ``` |
| |
| ## Individual Dataset Citations |
| |
| ### Tatoeba |
| ```bibtex |
| @inproceedings{artetxe2019massively, |
| title={Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond}, |
| author={Artetxe, Mikel and Schwenk, Holger}, |
| booktitle={Transactions of the Association for Computational Linguistics}, |
| year={2019} |
| } |
| ``` |
| |
| ### BUCC |
| ```bibtex |
| @inproceedings{zweigenbaum2017overview, |
| title={Overview of the second BUCC shared task: Spotting parallel sentences in comparable corpora}, |
| author={Zweigenbaum, Pierre and Sharoff, Serge and Rapp, Reinhard}, |
| booktitle={Proceedings of the 10th workshop on building and using comparable corpora}, |
| year={2017} |
| } |
| ``` |
| |
| *Additional citations available in the original MTEB task metadata and individual dataset pages.* |
| |
| ## Dataset Statistics |
| |
| ### Language Coverage |
| - **Total unique language codes**: 300+ |
| - **Language families**: Indo-European, Sino-Tibetan, Afro-Asiatic, Austronesian, Dravidian, and many more |
| - **Coverage**: High-resource (English, French, German, Spanish, Chinese, etc.), mid-resource (Hindi, Bengali, Tamil, etc.), and low-resource languages |
| |
| ### Split Distribution |
| - **Total splits**: 332 (each representing a specific language pair or configuration) |
| - **Examples per split**: Ranges from 228 to 8,750, with most splits containing 500-1,000 examples |
| |
| ### Data Quality |
| - All sentence pairs have been validated to contain non-empty `sentence1` and `sentence2` fields |
| - Language codes are preserved from original datasets |
| - Source attribution maintained for every example |
| |
| ## License |
| |
| This aggregated dataset inherits the licenses from its source datasets. Most MTEB datasets are released under permissive licenses (Apache 2.0, MIT, CC-BY, etc.). Please refer to the original dataset pages for specific licensing information. |
| |
| ## Acknowledgments |
| |
| - **MTEB Team**: For creating and maintaining the benchmark |
| - **Original Dataset Creators**: For providing high-quality bitext mining datasets |
| - **Hugging Face**: For dataset hosting and infrastructure |
| |
| ## Version History |
| |
| - **v2.0 (2026-04-02)**: Full release |
| - 10 source datasets (configs) |
| - 332 splits (all language pairs) |
| - 448,229 sentence pairs |
| - 300+ language codes |
| |
| - **v1.0 (2026-04-02)**: Initial partial release (deprecated) |
| - Only loaded default configs |
| - 8 source datasets |
| - 139,457 examples |
| |
| ## Contact |
| |
| For questions or issues with this aggregated dataset, please open an issue on the repository or contact the dataset creator. |
| |
