Update README.md

README.md

@@ -100,262 +100,11 @@ The dataset contains gzipped tab delimited text files for each direction.  Each
 
 The dataset contains 248 language pairs.
 
-Columns are:
-source_sentence target_sentence laser_score source_sentence_lid target_sentence_lid where lid is language classification probability
-
-Here are the sentence counts for each pair:\
-1621007	afr-eng \
-1172757	afr-som \
-497739	amh-eng\
-1888196	amh-fra\
-566422	amh-nya\
-89763	amh-orm\
-844829	amh-sna\
-491233	amh-som\
-52337	amh-ssw\
-1013477	amh-swh\
-257342	amh-tsn\
-231190	amh-tso\
-99902	amh-umb\
-508311	amh-xho\
-399634	amh-yor\
-834986	amh-zul\
-1372999	eng-fuv\
-2309758	eng-hau\
-172973	eng-ibo\
-1656141	eng-kam\
-9732858	eng-kin\
-2890688	eng-lin\
-3450573	eng-lug\
-2767100	eng-luo\
-3043677	eng-nso\
-1548650	eng-nya\
-2793755	eng-orm\
-8782707	eng-sna\
-576601	eng-som\
-165712	eng-ssw\
-23358739	eng-swh\
-5931529	eng-tsn\
-630860	eng-tso\
-302901	eng-umb\
-95678	eng-wol\
-8690985	eng-xho\
-1455571	eng-yor\
-3862020	eng-zul\
-372003	fra-hau\
-630593	fra-ibo\
-198309	fra-kam\
-1289491	fra-kin\
-347026	fra-lin\
-377017	fra-lug\
-295465	fra-luo\
-321118	fra-nso\
-1170250	fra-nya\
-319649	fra-orm\
-1256559	fra-som\
-119523	fra-ssw\
-2607867	fra-swh\
-630801	fra-tsn\
-440861	fra-tso\
-236624	fra-umb\
-189659	fra-wol\
-1092123	fra-xho\
-1760905	fra-zul\
-227958	fuv-hau\
-89652	fuv-ibo\
-13571	fuv-kam\
-192596	fuv-kin\
-79341	fuv-lug\
-50756	fuv-luo\
-42429	fuv-nso\
-189176	fuv-nya
-67398	fuv-orm\
-106809	fuv-sna\
-203640	fuv-som\
-19283	fuv-ssw\
-275428	fuv-swh\
-74068	fuv-tsn\
-55015	fuv-tso\
-27888	fuv-umb\
-138286	fuv-xho\
-331301	fuv-yor\
-150846	fuv-zul\
-247694	hau-ibo\
-90033	hau-kam\
-317291	hau-kin\
-169056	hau-lug\
-152246	hau-luo\
-158432	hau-nso\
-1141968	hau-nya\
-101928	hau-orm\
-780160	hau-sna\
-490683	hau-som\
-73076	hau-ssw\
-893732	hau-swh\
-265892	hau-tsn\
-213552	hau-tso\
-111124	hau-umb\
-596312	hau-xho\
-762819	hau-yor\
-796053	hau-zul\
-33966	ibo-kam\
-154467	ibo-kin\
-91272	ibo-lug\
-71387	ibo-luo\
-81767	ibo-nso\
-486357	ibo-nya\
-52249	ibo-orm\
-444070	ibo-sna\
-337727	ibo-som\
-36426	ibo-ssw\
-479101	ibo-swh\
-131142	ibo-tsn\
-99214	ibo-tso\
-48163	ibo-umb\
-323382	ibo-xho\
-378378	ibo-yor\
-491925	ibo-zul\
-74809	kam-kin\
-52158	kam-lug\
-39193	kam-luo\
-35061	kam-nso\
-92704	kam-nya\
-33964	kam-orm\
-94385	kam-sna\
-84297	kam-som\
-16222	kam-ssw\
-223474	kam-swh\
-69242	kam-tsn\
-73198	kam-tso\
-41157	kam-umb\
-80998	kam-xho\
-69432	kam-yor\
-114922	kam-zul\
-188222	kin-lug\
-157234	kin-luo\
-196675	kin-nso\
-389725	kin-nya\
-101820	kin-orm\
-385576	kin-sna\
-258130	kin-som\
-85684	kin-ssw\
-743661	kin-swh\
-268221	kin-tsn\
-315691	kin-tso\
-122759	kin-umb\
-361464	kin-xho\
-213902	kin-yor\
-492158	kin-zul\
-105776	lug-luo\
-107569	lug-nso\
-183247	lug-nya\
-64732	lug-orm\
-197359	lug-sna\
-131828	lug-som\
-51518	lug-ssw\
-325122	lug-swh\
-175387	lug-tsn\
-148662	lug-tso\
-75469	lug-umb\
-154149	lug-xho\
-137179	lug-yor\
-194564	lug-zul\
-87376	luo-nso\
-166259	luo-nya\
-48212	luo-orm\
-204663	luo-sna\
-123244	luo-som\
-38356	luo-ssw\
-324826	luo-swh\
-133960	luo-tsn\
-132306	luo-tso\
-68896	luo-umb\
-143748	luo-xho\
-110753	luo-yor\
-196325	luo-zul\
-154111	nso-nya\
-70340	nso-orm\
-155175	nso-sna\
-130594	nso-som\
-74696	nso-ssw\
-307206	nso-swh\
-234768	nso-tsn\
-212052	nso-tso\
-63006	nso-umb\
-200563	nso-xho\
-148906	nso-yor\
-230661	nso-zul\
-82514	nya-orm\
-976015	nya-sna\
-516451	nya-som\
-76598	nya-ssw\
-1078568	nya-swh\
-276998	nya-tsn\
-350167	nya-tso\
-141972	nya-umb\
-698857	nya-xho\
-512418	nya-yor\
-1062461	nya-zul\
-91493	orm-sna\
-83049	orm-som\
-31701	orm-ssw\
-178212	orm-swh\
-97553	orm-tsn\
-78559	orm-tso\
-44331	orm-umb\
-95505	orm-xho\
-73868	orm-yor\
-92733	orm-zul\
-511185	sna-som\
-76168	sna-ssw\
-1095473	sna-swh\
-287574	sna-tsn\
-336898	sna-tso\
-152770	sna-umb\
-842612	sna-xho\
-524739	sna-yor\
-1160370	sna-zul\
-61247	som-ssw\
-604372	som-swh\
-179485	som-tsn\
-177327	som-tso\
-93461	som-umb\
-69318	som-wol\
-362513	som-xho\
-355099	som-yor\
-506404	som-zul\
-147869	ssw-swh\
-85369	ssw-tsn\
-101540	ssw-tso\
-29533	ssw-umb\
-97437	ssw-xho\
-66000	ssw-yor\
-142991	ssw-zul\
-480942	swh-tsn\
-553410	swh-tso\
-276967	swh-umb\
-785796	swh-xho\
-559321	swh-yor\
-1240423	swh-zul\
-285124	tsn-tso\
-107024	tsn-umb\
-287133	tsn-xho\
-194308	tsn-yor\
-341119	tsn-zul\
-128803	tso-umb\
-383556	tso-xho\
-168359	tso-yor\
-471398	tso-zul\
-132264	umb-xho\
-81309	umb-yor\
-181634	umb-zul\
-371261	xho-yor\
-1066327	xho-zul\
-560858	yor-zul
+Sentence counts for each pair can be found [here](sentence_counts.txt).
 
 ### Data Fields
 
-Every instance for a language pair contains the following fields: 'translation' (containing sentence pairs), 'laser_score', 'source_sentence_lid', 'target_sentence_lid'.
+Every instance for a language pair contains the following fields: 'translation' (containing sentence pairs), 'laser_score', 'source_sentence_lid', 'target_sentence_lid', where 'lid' is language classification probability.
 
 Example:
 ```