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#				AUTOMATIC EvALL TSV REPORT
#
#	We kindly ask you to cite the following work when using EvALL:
#			EvALL: Open Access Evaluation for Information Access Systems
#			Enrique Amigó, Jorge Carrillo-de-Albornoz, Mario Almagro, Julio Gonzalo,
#			Javier Rodrguez-Vidal, Felisa Verdejo
#			In proceedings of SIGIR'17
#
#	This file contains the results for all measures and for all systems. Systems included are:
#			• task2_2539404758.tsv, whose original name is task2_2539404758.tsv_en
#			• task2_AI-UPV_1.tsv_e, whose original name is task2_AI-UPV_1.tsv_en
#			• task2_AI-UPV_2.tsv_e, whose original name is task2_AI-UPV_2.tsv_en
#			• task2_AI-UPV_3.tsv_e, whose original name is task2_AI-UPV_3.tsv_en
#			• task2_AIT_FHSTP_1.ts, whose original name is task2_AIT_FHSTP_1.tsv_en
#			• task2_AIT_FHSTP_2.ts, whose original name is task2_AIT_FHSTP_2.tsv_en
#			• task2_AIT_FHSTP_3.ts, whose original name is task2_AIT_FHSTP_3.tsv_en
#			• task2_avacaondata_1., whose original name is task2_avacaondata_1.tsv_en
#			• task2_avacaondata_2., whose original name is task2_avacaondata_2.tsv_en
#			• task2_avacaondata_3., whose original name is task2_avacaondata_3.tsv_en
#			• task2_BASELINE.tsv_e, whose original name is task2_BASELINE.tsv_en
#			• task2_besiguenza_1.t, whose original name is task2_besiguenza_1.tsv_en
#			• task2_ELiRF-VRAIN_1., whose original name is task2_ELiRF-VRAIN_1.tsv_en
#			• task2_ELiRF-VRAIN_2., whose original name is task2_ELiRF-VRAIN_2.tsv_en
#			• task2_ELiRF-VRAIN_3., whose original name is task2_ELiRF-VRAIN_3.tsv_en
#			• task2_I2C_1.tsv_en, whose original name is task2_I2C_1.tsv_en
#			• task2_LPtower_1.csv_, whose original name is task2_LPtower_1.csv_en
#			• task2_LPtower_2_majo, whose original name is task2_LPtower_2_major.csv_en
#			• task2_LPtower_3.csv_, whose original name is task2_LPtower_3.csv_en
#			• task2_multiaztertest, whose original name is task2_multiaztertest_1.tsv_en
#			• task2_NIT Agartala N, whose original name is task2_NIT Agartala NLP Team_1.tsv_en
#			• task2_shm2022_1.tsv_, whose original name is task2_shm2022_1.tsv_en
#			• task2_ThangCIC_2.tsv, whose original name is task2_ThangCIC_2.tsv_en
#			• task2_ThangCIC_4.tsv, whose original name is task2_ThangCIC_4.tsv_en
#			• task2_ThangCIC_8.tsv, whose original name is task2_ThangCIC_8.tsv_en
#			• task2_UMU_1_en, whose original name is task2_UMU_1_en
#			• task2_UMU_2_en, whose original name is task2_UMU_2_en
#			• task2_UMU_3_en, whose original name is task2_UMU_3_en
#			• task2_UNED-UPM_1.tsv, whose original name is task2_UNED-UPM_1.tsv_en
#			• task2_UNED-UPM_2.tsv, whose original name is task2_UNED-UPM_2.tsv_en
#
#	The next table contains the average result across test case for each measure. 
#	Those measures that do not satisfy the preconditions are marked with -. 
#	Only results of test case present in the gold are taken into account.
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#	 The measures included in the table are:
#		- Accuracy - Acc
#		- Precision - P
#		- Recall - R
#		- F Measure - F(P, R)
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"Output Name"	"Acc"	"P"	"R"	"F(P, R)"
"task2_2539404758.tsv_en"	"0,6578"	"0,4667"	"0,4186"	"0,4028"
"task2_AI-UPV_1.tsv_en"	"0,6730"	"0,5353"	"0,5177"	"0,4740"
"task2_AI-UPV_2.tsv_en"	"0,6977"	"0,5625"	"0,5514"	"0,5063"
"task2_AI-UPV_3.tsv_en"	"0,6996"	"0,5718"	"0,5631"	"0,5133"
"task2_AIT_FHSTP_1.tsv_en"	"0,6730"	"0,5125"	"0,4618"	"0,4441"
"task2_AIT_FHSTP_2.tsv_en"	"0,5323"	"0,4629"	"0,4194"	"0,3541"
"task2_AIT_FHSTP_3.tsv_en"	"0,6635"	"0,5196"	"0,4767"	"0,4545"
"task2_avacaondata_1.tsv_en"	"0,7471"	"0,6184"	"0,5532"	"0,5337"
"task2_avacaondata_2.tsv_en"	"0,6977"	"0,5491"	"0,5116"	"0,4838"
"task2_avacaondata_3.tsv_en"	"0,7471"	"0,6184"	"0,5532"	"0,5337"
"task2_BASELINE.tsv_en"	"0,5722"	"0,3836"	"0,3471"	"0,3276"
"task2_besiguenza_1.tsv_en"	"0,6464"	"0,5030"	"0,4573"	"0,4389"
"task2_ELiRF-VRAIN_1.tsv_en"	"0,7262"	"0,5843"	"0,5148"	"0,5028"
"task2_ELiRF-VRAIN_2.tsv_en"	"0,7319"	"0,5780"	"0,5272"	"0,5049"
"task2_ELiRF-VRAIN_3.tsv_en"	"0,7300"	"0,5954"	"0,5218"	"0,5084"
"task2_I2C_1.tsv_en"	"0,6654"	"0,5112"	"0,5193"	"0,4658"
"task2_LPtower_1.csv_en"	"0,6806"	"0,5289"	"0,4610"	"0,4515"
"task2_LPtower_2_major.csv_en"	"0,6654"	"0,5051"	"0,4557"	"0,4347"
"task2_LPtower_3.csv_en"	"0,3346"	"0,1860"	"0,1671"	"0,1577"
"task2_multiaztertest_1.tsv_en"	"0,7110"	"0,5520"	"0,4789"	"0,4689"
"task2_NIT Agartala NLP Team_1.tsv_en"	"0,6388"	"0,5303"	"0,2698"	"0,3052"
"task2_shm2022_1.tsv_en"	"0,1312"	"0,3109"	"0,1630"	"0,0490"
"task2_ThangCIC_2.tsv_en"	"0,6692"	"0,5232"	"0,4744"	"0,4585"
"task2_ThangCIC_4.tsv_en"	"0,6768"	"0,5178"	"0,4648"	"0,4472"
"task2_ThangCIC_8.tsv_en"	"0,6939"	"0,5490"	"0,5058"	"0,4792"
"task2_UMU_1_en"	"0,6920"	"0,5296"	"0,4773"	"0,4594"
"task2_UMU_2_en"	"0,7091"	"0,5461"	"0,4899"	"0,4751"
"task2_UMU_3_en"	"0,7015"	"0,5482"	"0,4693"	"0,4644"
"task2_UNED-UPM_1.tsv_en"	"0,5380"	"0,4060"	"0,4250"	"0,3635"
"task2_UNED-UPM_2.tsv_en"	"0,4848"	"0,3768"	"0,3878"	"0,3273"
"Majority Class"	"0,5932"	"0,5932"	"0,1429"	"0,1064"