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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_es
#			• task2_AI-UPV_1.tsv_e, whose original name is task2_AI-UPV_1.tsv_es
#			• task2_AI-UPV_2.tsv_e, whose original name is task2_AI-UPV_2.tsv_es
#			• task2_AI-UPV_3.tsv_e, whose original name is task2_AI-UPV_3.tsv_es
#			• task2_AIT_FHSTP_1.ts, whose original name is task2_AIT_FHSTP_1.tsv_es
#			• task2_AIT_FHSTP_2.ts, whose original name is task2_AIT_FHSTP_2.tsv_es
#			• task2_AIT_FHSTP_3.ts, whose original name is task2_AIT_FHSTP_3.tsv_es
#			• task2_avacaondata_1., whose original name is task2_avacaondata_1.tsv_es
#			• task2_avacaondata_2., whose original name is task2_avacaondata_2.tsv_es
#			• task2_avacaondata_3., whose original name is task2_avacaondata_3.tsv_es
#			• task2_BASELINE.tsv_e, whose original name is task2_BASELINE.tsv_es
#			• task2_besiguenza_1.t, whose original name is task2_besiguenza_1.tsv_es
#			• task2_ELiRF-VRAIN_1., whose original name is task2_ELiRF-VRAIN_1.tsv_es
#			• task2_ELiRF-VRAIN_2., whose original name is task2_ELiRF-VRAIN_2.tsv_es
#			• task2_ELiRF-VRAIN_3., whose original name is task2_ELiRF-VRAIN_3.tsv_es
#			• task2_I2C_1.tsv_es, whose original name is task2_I2C_1.tsv_es
#			• task2_LPtower_1.csv_, whose original name is task2_LPtower_1.csv_es
#			• task2_LPtower_2_majo, whose original name is task2_LPtower_2_major.csv_es
#			• task2_LPtower_3.csv_, whose original name is task2_LPtower_3.csv_es
#			• task2_multiaztertest, whose original name is task2_multiaztertest_1.tsv_es
#			• task2_NIT Agartala N, whose original name is task2_NIT Agartala NLP Team_1.tsv_es
#			• task2_shm2022_1.tsv_, whose original name is task2_shm2022_1.tsv_es
#			• task2_ThangCIC_2.tsv, whose original name is task2_ThangCIC_2.tsv_es
#			• task2_ThangCIC_4.tsv, whose original name is task2_ThangCIC_4.tsv_es
#			• task2_ThangCIC_8.tsv, whose original name is task2_ThangCIC_8.tsv_es
#			• task2_UMU_1_es, whose original name is task2_UMU_1_es
#			• task2_UMU_2_es, whose original name is task2_UMU_2_es
#			• task2_UMU_3_es, whose original name is task2_UMU_3_es
#			• task2_UNED-UPM_1.tsv, whose original name is task2_UNED-UPM_1.tsv_es
#			• task2_UNED-UPM_2.tsv, whose original name is task2_UNED-UPM_2.tsv_es
#
#	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_es"	"0,5733"	"0,4376"	"0,3689"	"0,3570"
"task2_AI-UPV_1.tsv_es"	"0,5526"	"0,4501"	"0,4250"	"0,3893"
"task2_AI-UPV_2.tsv_es"	"0,5545"	"0,4754"	"0,4405"	"0,3974"
"task2_AI-UPV_3.tsv_es"	"0,5545"	"0,4754"	"0,4405"	"0,3974"
"task2_AIT_FHSTP_1.tsv_es"	"0,6109"	"0,4975"	"0,4515"	"0,4235"
"task2_AIT_FHSTP_2.tsv_es"	"0,5188"	"0,4832"	"0,4072"	"0,3587"
"task2_AIT_FHSTP_3.tsv_es"	"0,6410"	"0,5416"	"0,5215"	"0,4775"
"task2_avacaondata_1.tsv_es"	"0,6560"	"0,5718"	"0,5169"	"0,4864"
"task2_avacaondata_2.tsv_es"	"0,6241"	"0,5505"	"0,5044"	"0,4672"
"task2_avacaondata_3.tsv_es"	"0,6560"	"0,5718"	"0,5169"	"0,4864"
"task2_BASELINE.tsv_es"	"0,5846"	"0,4827"	"0,3317"	"0,3488"
"task2_besiguenza_1.tsv_es"	"0,6109"	"0,4837"	"0,3891"	"0,3965"
"task2_ELiRF-VRAIN_1.tsv_es"	"0,6767"	"0,5818"	"0,4964"	"0,4841"
"task2_ELiRF-VRAIN_2.tsv_es"	"0,6410"	"0,5500"	"0,4653"	"0,4494"
"task2_ELiRF-VRAIN_3.tsv_es"	"0,6786"	"0,5891"	"0,4881"	"0,4867"
"task2_I2C_1.tsv_es"	"0,6278"	"0,5432"	"0,5152"	"0,4714"
"task2_LPtower_1.csv_es"	"0,6335"	"0,5666"	"0,4889"	"0,4709"
"task2_LPtower_2_major.csv_es"	"0,6090"	"0,5207"	"0,4353"	"0,4240"
"task2_LPtower_3.csv_es"	"0,2876"	"0,1682"	"0,1400"	"0,1404"
"task2_multiaztertest_1.tsv_es"	"0,6466"	"0,5457"	"0,4863"	"0,4679"
"task2_NIT Agartala NLP Team_1.tsv_es"	"0,6071"	"0,6269"	"0,2878"	"0,3210"
"task2_shm2022_1.tsv_es"	"0,1447"	"0,4268"	"0,1651"	"0,0630"
"task2_ThangCIC_2.tsv_es"	"0,6560"	"0,5429"	"0,4604"	"0,4514"
"task2_ThangCIC_4.tsv_es"	"0,6316"	"0,5494"	"0,5131"	"0,4699"
"task2_ThangCIC_8.tsv_es"	"0,6316"	"0,5472"	"0,4962"	"0,4639"
"task2_UMU_1_es"	"0,6541"	"0,5985"	"0,5026"	"0,4855"
"task2_UMU_2_es"	"0,6447"	"0,5680"	"0,4986"	"0,4721"
"task2_UMU_3_es"	"0,6429"	"0,5559"	"0,4948"	"0,4687"
"task2_UNED-UPM_1.tsv_es"	"0,5169"	"0,4235"	"0,4296"	"0,3726"
"task2_UNED-UPM_2.tsv_es"	"0,5000"	"0,3672"	"0,3677"	"0,3263"
"Majority Class"	"0,5150"	"0,5150"	"0,1429"	"0,0971"