%------------------------------------------------------------------------------
% File : GKC---0.8
% Problem : CSR115+44 : TPTP v8.1.2. Released v4.0.0.
% Transfm : none
% Format : tptp:raw
% Command : gkc %s
% Computer : n028.cluster.edu
% Model : x86_64 x86_64
% CPU : Intel(R) Xeon(R) CPU E5-2620 v4 2.10GHz
% Memory : 8042.1875MB
% OS : Linux 3.10.0-693.el7.x86_64
% CPULimit : 300s
% WCLimit : 300s
% DateTime : Wed Aug 30 21:24:29 EDT 2023
% Result : Theorem 1.30s 0.68s
% Output : CNFRefutation 1.30s
% Verified :
% SZS Type : -
% Comments :
%------------------------------------------------------------------------------
%----WARNING: Could not form TPTP format derivation
%------------------------------------------------------------------------------
%----ORIGINAL SYSTEM OUTPUT
% 0.11/0.12 % Problem : CSR115+44 : TPTP v8.1.2. Released v4.0.0.
% 0.11/0.13 % Command : gkc %s
% 0.13/0.34 % Computer : n028.cluster.edu
% 0.13/0.34 % Model : x86_64 x86_64
% 0.13/0.34 % CPU : Intel(R) Xeon(R) CPU E5-2620 v4 @ 2.10GHz
% 0.13/0.34 % Memory : 8042.1875MB
% 0.13/0.34 % OS : Linux 3.10.0-693.el7.x86_64
% 0.13/0.34 % CPULimit : 300
% 0.13/0.34 % WCLimit : 300
% 0.13/0.34 % DateTime : Mon Aug 28 12:35:39 EDT 2023
% 0.13/0.34 % CPUTime :
% 0.20/0.46
% 0.20/0.46 input clause set summed statistics:
% 0.20/0.46 ----------------------------------
% 0.20/0.46 in_clause_count: 10590
% 0.20/0.46 in_rule_clause_count: 337
% 0.20/0.46 in_fact_clause_count: 10253
% 0.20/0.46 in_answer_clause_count: 0
% 0.20/0.46 in_ground_clause_count: 10254
% 0.20/0.46 in_unit_clause_count: 10256
% 0.20/0.46 in_horn_clause_count: 10580
% 0.20/0.46 in_pos_clause_count: 10260
% 0.20/0.46 in_neg_clause_count: 11
% 0.20/0.46 in_poseq_clause_count: 0
% 0.20/0.46 in_negeq_clause_count: 0
% 0.20/0.46 in_unitposeq_clause_count: 0
% 0.20/0.46 in_chain_clause_count: 0
% 0.20/0.46 in_min_length: 1
% 0.20/0.46 in_max_length: 9
% 0.20/0.46 in_min_depth: 1
% 0.20/0.46 in_max_depth: 5
% 0.20/0.46 in_min_size: 3
% 0.20/0.46 in_max_size: 30
% 0.20/0.46 in_min_vars: 0
% 0.20/0.46 in_max_vars: 7
% 0.20/0.46 in_extaxiom_count: 10394
% 0.20/0.46 in_axiom_count: 0
% 0.20/0.46 in_assumption_count: 195
% 0.20/0.46 in_goal_count: 1
% 0.20/0.46 in_neg_goal_count: 1
% 0.20/0.46 in_pos_goal_count: 0
% 0.20/0.46 in_posunit_goal_count: 0
% 0.20/0.46
% 0.20/0.46 auto guide:
% 0.20/0.46 -----------
% 0.20/0.46 {
% 0.20/0.46 "print":1,
% 0.20/0.46 "print_level": 15,
% 0.20/0.46 "max_size": 0,
% 0.20/0.46 "max_depth": 0,
% 0.20/0.46 "max_length": 0,
% 0.20/0.46 "max_dseconds": 0,
% 0.20/0.46 "equality":0,
% 0.20/0.46 "runs":[
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0, "sine":5},
% 0.20/0.46 {"max_dseconds":1, "strategy":["hardness_pref"], "query_preference":0, "sine":5},
% 0.20/0.46 {"max_dseconds":1, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":1, "strategy":["hardness_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus", "positive_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus", "max_ground_weight"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "weight_select_ratio":100, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus", "double"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0, "sine":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["hardness_pref"], "query_preference":0, "weight_select_ratio":20, "depth_penalty":50, "length_penalty":100},
% 0.20/0.46 {"max_dseconds":1, "strategy":["hardness_pref", "max_ground_weight"], "query_preference":0},
% 0.20/0.46 {"length_penalty":100, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":1},
% 0.20/0.46 {"strategy":["hardness_pref", "max_weight"], "length_penalty":100, "depth_penalty":50, "max_depth":3, "var_weight":10, "repeat_var_weight":10, "max_dseconds":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["positive_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1, "depth_penalty":100},
% 0.20/0.46 {"var_weight":70, "repeat_var_weight":70, "max_depth":3, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["unit"], "query_preference":1, "reverse_clauselist":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":3},
% 0.20/0.46 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0, "weight_select_ratio":100, "depth_penalty":100, "length_penalty":100},
% 0.20/0.46 {"max_dseconds":1, "strategy":["unit"], "query_preference":0, "var_weight":1, "depth_penalty":100, "repeat_var_weight":1},
% 0.20/0.46 {"weight_select_ratio":100, "length_penalty":100, "query_preference":1, "strategy":["query_focus"], "max_dseconds":1},
% 0.20/0.46
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0, "sine":5},
% 0.20/0.46 {"max_dseconds":10, "strategy":["hardness_pref"], "query_preference":0, "sine":5},
% 0.20/0.46 {"max_dseconds":10, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":10, "strategy":["hardness_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus", "positive_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus", "max_ground_weight"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "weight_select_ratio":100, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus", "double"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0, "sine":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["hardness_pref"], "query_preference":0, "weight_select_ratio":20, "depth_penalty":50, "length_penalty":100},
% 0.20/0.46 {"max_dseconds":10, "strategy":["hardness_pref", "max_ground_weight"], "query_preference":0},
% 0.20/0.46 {"length_penalty":100, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":10},
% 0.20/0.46 {"strategy":["hardness_pref", "max_weight"], "length_penalty":100, "depth_penalty":50, "max_depth":3, "var_weight":10, "repeat_var_weight":10, "max_dseconds":10},
% 0.20/0.46 {"max_dseconds":10, "strategy":["positive_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1, "depth_penalty":100},
% 0.20/0.46 {"var_weight":70, "repeat_var_weight":70, "max_depth":3, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":10},
% 0.20/0.46 {"max_dseconds":10, "strategy":["unit"], "query_preference":1, "reverse_clauselist":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":3},
% 0.20/0.46 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0, "weight_select_ratio":100, "depth_penalty":100, "length_penalty":100},
% 0.20/0.46 {"max_dseconds":10, "strategy":["unit"], "query_preference":0, "var_weight":1, "depth_penalty":100, "repeat_var_weight":1},
% 0.20/0.46 {"weight_select_ratio":100, "length_penalty":100, "query_preference":1, "strategy":["query_focus"], "max_dseconds":10},
% 0.20/0.46
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":50, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":50, "strategy":["hardness_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus", "positive_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus", "max_ground_weight"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "weight_select_ratio":100, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus", "double"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":0, "sine":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["hardness_pref"], "query_preference":0, "weight_select_ratio":20, "depth_penalty":50, "length_penalty":100},
% 0.20/0.46 {"max_dseconds":50, "strategy":["hardness_pref", "max_ground_weight"], "query_preference":0},
% 0.20/0.46 {"length_penalty":100, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":50},
% 0.20/0.46 {"strategy":["hardness_pref", "max_weight"], "length_penalty":100, "depth_penalty":50, "max_depth":3, "var_weight":10, "repeat_var_weight":10, "max_dseconds":50},
% 0.20/0.46 {"max_dseconds":50, "strategy":["positive_pref"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1, "depth_penalty":100},
% 0.20/0.46 {"var_weight":70, "repeat_var_weight":70, "max_depth":3, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":50},
% 0.20/0.46 {"max_dseconds":50, "strategy":["unit"], "query_preference":1, "reverse_clauselist":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":3},
% 0.20/0.46 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.46 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":0, "weight_select_ratio":100, "depth_penalty":100, "length_penalty":100},
% 0.20/0.46 {"max_dseconds":50, "strategy":["unit"], "query_preference":0, "var_weight":1, "depth_penalty":100, "repeat_var_weight":1},
% 0.20/0.46 {"weight_select_ratio":100, "length_penalty":100, "query_preference":1, "strategy":["query_focus"], "max_dseconds":50},
% 0.20/0.46
% 0.20/0.46 {"max_dseconds":250, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":250, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":250, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.46 {"max_dseconds":250, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":250, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.46 {"max_dseconds":250, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":250, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":250, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.46
% 0.20/0.46 {"max_dseconds":1250, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.46 {"max_dseconds":1250, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1250, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.46 {"max_dseconds":1250, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1250, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.46 {"max_dseconds":1250, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.46 {"max_dseconds":1250, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.46 {"max_dseconds":1250, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2}
% 0.20/0.46
% 0.20/0.46 ]}
% 0.20/0.46
% 0.20/0.46
% 0.20/0.46 **** run 1 fork 0 starts with strategy
% 0.20/0.46 {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":0}
% 0.20/0.46
% 0.20/0.46 **** run 2 fork 1 starts with strategy
% 0.20/0.46 {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":1}
% 0.20/0.46
% 0.20/0.46 **** run 3 fork 2 starts with strategy
% 0.20/0.46 {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":1,"sine":1}
% 0.20/0.46
% 0.20/0.46 **** run 4 fork 3 starts with strategy
% 0.20/0.46 {"max_dseconds":1,"strategy":["query_focus"],"query_preference":1}
% 0.20/0.46
% 0.20/0.46 **** run 5 fork 4 starts with strategy
% 0.20/0.46 {"max_dseconds":1,"strategy":["negative_pref"],"query_preference":1,"sine":2}
% 0.20/0.46
% 0.20/0.46 **** run 8 fork 7 starts with strategy
% 0.20/0.46 {"max_dseconds":1,"strategy":["negative_pref"],"query_preference":0,"sine":5}
% 0.20/0.47
% 0.20/0.47 **** run 6 fork 5 starts with strategy
% 0.20/0.47 {"max_dseconds":1,"strategy":["query_focus","positive_pref"],"query_preference":1}
% 0.20/0.47
% 0.20/0.47 **** run 7 fork 6 starts with strategy
% 0.20/0.47 {"max_dseconds":1,"strategy":["unit"],"query_preference":0,"sine":2}
% 0.20/0.61
% 0.20/0.61 fork 7: search finished without proof.
% 0.20/0.62
% 0.20/0.62 fork 5: search finished without proof.
% 0.20/0.62
% 0.20/0.62 fork 3: search finished without proof.
% 0.20/0.64
% 0.20/0.64 **** run 16 fork 7 starts with strategy
% 0.20/0.64 {"max_dseconds":1,"strategy":["query_focus"],"query_preference":1,"var_weight":1,"weight_select_ratio":100,"repeat_var_weight":1}
% 0.20/0.65
% 0.20/0.65 **** run 12 fork 3 starts with strategy
% 0.20/0.65 {"max_dseconds":1,"strategy":["hardness_pref"],"query_preference":0}
% 0.20/0.66
% 0.20/0.66 **** run 14 fork 5 starts with strategy
% 0.20/0.66 {"max_dseconds":1,"strategy":["negative_pref"],"query_preference":1}
% 1.30/0.68
% 1.30/0.68
% 1.30/0.68 result: proof found
% 1.30/0.68 for /export/starexec/sandbox/benchmark/theBenchmark.p
% 1.30/0.68 by run 1 fork 0 strategy {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":0}
% 1.30/0.68 % SZS status Theorem for /export/starexec/sandbox/benchmark/theBenchmark.p
% 1.30/0.68
% 1.30/0.68 % SZS output start CNFRefutation for /export/starexec/sandbox/benchmark/theBenchmark.p
% 1.30/0.68 fof('synth_qa07_007_mira_news_1253_$sk', plain, (~val(X7,bmw_0) | (~val(X1,bmw_0) | (~sub(X7,name_1_1) | (~sub(X2,firma_1_1) | (~sub(X1,name_1_1) | (~obj(X3,X2) | (~attr(X6,X5) | (~attr(X4,X7) | ~attr(X2,X1))))))))),
% 1.30/0.68 inference(negpush_and_skolemize,[],['synth_qa07_007_mira_news_1253'])).
% 1.30/0.68 fof('synth_qa07_007_mira_news_1253', conjecture, (? [X0,X1,X2,X3,X4,X5,X6] : ((((((((attr(X0,X1) & attr(X3,X2)) & attr(X5,X6)) & obj(X4,X0)) & sub(X1,name_1_1)) & sub(X0,firma_1_1)) & sub(X2,name_1_1)) & val(X1,bmw_0)) & val(X2,bmw_0))),
% 1.30/0.68 input).
% 1.30/0.68 fof('ave07_era5_synth_qa07_007_mira_news_1253_$sk', plain, (sort(gro__337m__374tig_1_1,nq) & (varia(c699,varia_c) & (refer(c699,refer_c) & (quant(c699,quant_c) & (gener(c699,gener_c) & (fact(c699,real) & (etype(c699,etype_c) & (card(c699,card_c) & (sort(c699,ent) & (sort(london_0,fe) & (varia(stadt__1_1,varia_c) & (refer(stadt__1_1,refer_c) & (quant(stadt__1_1,one) & (gener(stadt__1_1,ge) & (fact(stadt__1_1,real) & (etype(stadt__1_1,int0) & (card(stadt__1_1,int1) & (sort(stadt__1_1,io) & (sort(stadt__1_1,d) & (varia(c591,varia_c) & (refer(c591,indet) & (quant(c591,one) & (gener(c591,sp) & (fact(c591,real) & (etype(c591,int0) & (card(c591,int1) & (sort(c591,na) & (varia(c590,con) & (refer(c590,det) & (quant(c590,one) & (gener(c590,sp) & (fact(c590,real) & (etype(c590,int0) & (card(c590,int1) & (sort(c590,io) & (sort(c590,d) & (varia(nobelfirma_1_1,varia_c) & (refer(nobelfirma_1_1,refer_c) & (quant(nobelfirma_1_1,one) & (gener(nobelfirma_1_1,ge) & (fact(nobelfirma_1_1,real) & (etype(nobelfirma_1_1,int0) & (card(nobelfirma_1_1,int1) & (sort(nobelfirma_1_1,io) & (sort(nobelfirma_1_1,d) & (sort(britisch__1_1,nq) & (varia(c582,con) & (refer(c582,det) & (quant(c582,one) & (gener(c582,sp) & (fact(c582,real) & (etype(c582,int0) & (card(c582,int1) & (sort(c582,io) & (sort(c582,d) & (varia(einstieg_1_1,varia_c) & (refer(einstieg_1_1,refer_c) & (quant(einstieg_1_1,one) & (gener(einstieg_1_1,ge) & (fact(einstieg_1_1,real) & (etype(einstieg_1_1,int0) & (card(einstieg_1_1,int1) & (sort(einstieg_1_1,ad) & (varia(c573,varia_c) & (refer(c573,refer_c) & (quant(c573,one) & (gener(c573,gener_c) & (fact(c573,real) & (etype(c573,int0) & (card(c573,int1) & (sort(c573,ad) & (varia(kei_1_1,varia_c) & (refer(kei_1_1,refer_c) & (quant(kei_1_1,one) & (gener(kei_1_1,ge) & (fact(kei_1_1,real) & (etype(kei_1_1,int0) & (card(kei_1_1,int1) & (sort(kei_1_1,o) & (varia(c572,varia_c) & (refer(c572,indet) & (quant(c572,mult) & (gener(c572,gener_c) & (fact(c572,real) & (etype(c572,int1) & (card(c572,cons(x_constant,cons(int1,nil))) & (sort(c572,o) & (sort(royce_0,fe) & (varia(c571,varia_c) & (refer(c571,indet) & (quant(c571,one) & (gener(c571,sp) & (fact(c571,real) & (etype(c571,int0) & (card(c571,int1) & (sort(c571,na) & (varia(c570,con) & (refer(c570,det) & (quant(c570,one) & (gener(c570,sp) & (fact(c570,real) & (etype(c570,int0) & (card(c570,int1) & (sort(c570,d) & (sort(roll_0,fe) & (varia(familiename_1_1,varia_c) & (refer(familiename_1_1,refer_c) & (quant(familiename_1_1,one) & (gener(familiename_1_1,ge) & (fact(familiename_1_1,real) & (etype(familiename_1_1,int0) & (card(familiename_1_1,int1) & (sort(familiename_1_1,na) & (varia(mensch_1_1,varia_c) & (refer(mensch_1_1,refer_c) & (quant(mensch_1_1,one) & (gener(mensch_1_1,ge) & (fact(mensch_1_1,real) & (etype(mensch_1_1,int0) & (card(mensch_1_1,int1) & (sort(mensch_1_1,d) & (varia(c565,varia_c) & (refer(c565,indet) & (quant(c565,one) & (gener(c565,sp) & (fact(c565,real) & (etype(c565,int0) & (card(c565,int1) & (sort(c565,na) & (varia(c564,con) & (refer(c564,det) & (quant(c564,one) & (gener(c564,sp) & (fact(c564,real) & (etype(c564,int0) & (card(c564,int1) & (sort(c564,d) & (sort(bmw_0,fe) & (varia(name_1_1,varia_c) & (refer(name_1_1,refer_c) & (quant(name_1_1,one) & (gener(name_1_1,ge) & (fact(name_1_1,real) & (etype(name_1_1,int0) & (card(name_1_1,int1) & (sort(name_1_1,na) & (varia(firma_1_1,varia_c) & (refer(firma_1_1,refer_c) & (quant(firma_1_1,one) & (gener(firma_1_1,ge) & (fact(firma_1_1,real) & (etype(firma_1_1,int0) & (card(firma_1_1,int1) & (sort(firma_1_1,io) & (sort(firma_1_1,d) & (varia(c558,varia_c) & (refer(c558,indet) & (quant(c558,one) & (gener(c558,sp) & (fact(c558,real) & (etype(c558,int0) & (card(c558,int1) & (sort(c558,na) & (varia(c557,con) & (refer(c557,det) & (quant(c557,one) & (gener(c557,sp) & (fact(c557,real) & (etype(c557,int0) & (card(c557,int1) & (sort(c557,io) & (sort(c557,d) & (sub(nobelfirma_1_1,firma_1_1) & (assoc(nobelfirma_1_1,gro__337m__374tig_1_1) & (tupl_p8(c699,c557,c564,c570,c572,c573,c582,c590) & (val(c591,london_0) & (sub(c591,name_1_1) & (sub(c590,stadt__1_1) & (attr(c590,c591) & (sub(c582,nobelfirma_1_1) & (prop(c582,britisch__1_1) & (subs(c573,einstieg_1_1) & (pred(c572,kei_1_1) & (val(c571,royce_0) & (sub(c571,familiename_1_1) & (sub(c570,mensch_1_1) & (attr(c570,c571) & (val(c565,roll_0) & (sub(c565,familiename_1_1) & (sub(c564,mensch_1_1) & (attr(c564,c565) & (val(c558,bmw_0) & (sub(c558,name_1_1) & (sub(c557,firma_1_1) & attr(c557,c558))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))),
% 1.30/0.68 inference(negpush_and_skolemize,[],['ave07_era5_synth_qa07_007_mira_news_1253'])).
% 1.30/0.68 fof('ave07_era5_synth_qa07_007_mira_news_1253', hypothesis, ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((attr(c557,c558) & sub(c557,firma_1_1)) & sub(c558,name_1_1)) & val(c558,bmw_0)) & attr(c564,c565)) & sub(c564,mensch_1_1)) & sub(c565,familiename_1_1)) & val(c565,roll_0)) & attr(c570,c571)) & sub(c570,mensch_1_1)) & sub(c571,familiename_1_1)) & val(c571,royce_0)) & pred(c572,kei_1_1)) & subs(c573,einstieg_1_1)) & prop(c582,britisch__1_1)) & sub(c582,nobelfirma_1_1)) & attr(c590,c591)) & sub(c590,stadt__1_1)) & sub(c591,name_1_1)) & val(c591,london_0)) & tupl_p8(c699,c557,c564,c570,c572,c573,c582,c590)) & assoc(nobelfirma_1_1,gro__337m__374tig_1_1)) & sub(nobelfirma_1_1,firma_1_1)) & sort(c557,d)) & sort(c557,io)) & card(c557,int1)) & etype(c557,int0)) & fact(c557,real)) & gener(c557,sp)) & quant(c557,one)) & refer(c557,det)) & varia(c557,con)) & sort(c558,na)) & card(c558,int1)) & etype(c558,int0)) & fact(c558,real)) & gener(c558,sp)) & quant(c558,one)) & refer(c558,indet)) & varia(c558,varia_c)) & sort(firma_1_1,d)) & sort(firma_1_1,io)) & card(firma_1_1,int1)) & etype(firma_1_1,int0)) & fact(firma_1_1,real)) & gener(firma_1_1,ge)) & quant(firma_1_1,one)) & refer(firma_1_1,refer_c)) & varia(firma_1_1,varia_c)) & sort(name_1_1,na)) & card(name_1_1,int1)) & etype(name_1_1,int0)) & fact(name_1_1,real)) & gener(name_1_1,ge)) & quant(name_1_1,one)) & refer(name_1_1,refer_c)) & varia(name_1_1,varia_c)) & sort(bmw_0,fe)) & sort(c564,d)) & card(c564,int1)) & etype(c564,int0)) & fact(c564,real)) & gener(c564,sp)) & quant(c564,one)) & refer(c564,det)) & varia(c564,con)) & sort(c565,na)) & card(c565,int1)) & etype(c565,int0)) & fact(c565,real)) & gener(c565,sp)) & quant(c565,one)) & refer(c565,indet)) & varia(c565,varia_c)) & sort(mensch_1_1,d)) & card(mensch_1_1,int1)) & etype(mensch_1_1,int0)) & fact(mensch_1_1,real)) & gener(mensch_1_1,ge)) & quant(mensch_1_1,one)) & refer(mensch_1_1,refer_c)) & varia(mensch_1_1,varia_c)) & sort(familiename_1_1,na)) & card(familiename_1_1,int1)) & etype(familiename_1_1,int0)) & fact(familiename_1_1,real)) & gener(familiename_1_1,ge)) & quant(familiename_1_1,one)) & refer(familiename_1_1,refer_c)) & varia(familiename_1_1,varia_c)) & sort(roll_0,fe)) & sort(c570,d)) & card(c570,int1)) & etype(c570,int0)) & fact(c570,real)) & gener(c570,sp)) & quant(c570,one)) & refer(c570,det)) & varia(c570,con)) & sort(c571,na)) & card(c571,int1)) & etype(c571,int0)) & fact(c571,real)) & gener(c571,sp)) & quant(c571,one)) & refer(c571,indet)) & varia(c571,varia_c)) & sort(royce_0,fe)) & sort(c572,o)) & card(c572,cons(x_constant,cons(int1,nil)))) & etype(c572,int1)) & fact(c572,real)) & gener(c572,gener_c)) & quant(c572,mult)) & refer(c572,indet)) & varia(c572,varia_c)) & sort(kei_1_1,o)) & card(kei_1_1,int1)) & etype(kei_1_1,int0)) & fact(kei_1_1,real)) & gener(kei_1_1,ge)) & quant(kei_1_1,one)) & refer(kei_1_1,refer_c)) & varia(kei_1_1,varia_c)) & sort(c573,ad)) & card(c573,int1)) & etype(c573,int0)) & fact(c573,real)) & gener(c573,gener_c)) & quant(c573,one)) & refer(c573,refer_c)) & varia(c573,varia_c)) & sort(einstieg_1_1,ad)) & card(einstieg_1_1,int1)) & etype(einstieg_1_1,int0)) & fact(einstieg_1_1,real)) & gener(einstieg_1_1,ge)) & quant(einstieg_1_1,one)) & refer(einstieg_1_1,refer_c)) & varia(einstieg_1_1,varia_c)) & sort(c582,d)) & sort(c582,io)) & card(c582,int1)) & etype(c582,int0)) & fact(c582,real)) & gener(c582,sp)) & quant(c582,one)) & refer(c582,det)) & varia(c582,con)) & sort(britisch__1_1,nq)) & sort(nobelfirma_1_1,d)) & sort(nobelfirma_1_1,io)) & card(nobelfirma_1_1,int1)) & etype(nobelfirma_1_1,int0)) & fact(nobelfirma_1_1,real)) & gener(nobelfirma_1_1,ge)) & quant(nobelfirma_1_1,one)) & refer(nobelfirma_1_1,refer_c)) & varia(nobelfirma_1_1,varia_c)) & sort(c590,d)) & sort(c590,io)) & card(c590,int1)) & etype(c590,int0)) & fact(c590,real)) & gener(c590,sp)) & quant(c590,one)) & refer(c590,det)) & varia(c590,con)) & sort(c591,na)) & card(c591,int1)) & etype(c591,int0)) & fact(c591,real)) & gener(c591,sp)) & quant(c591,one)) & refer(c591,indet)) & varia(c591,varia_c)) & sort(stadt__1_1,d)) & sort(stadt__1_1,io)) & card(stadt__1_1,int1)) & etype(stadt__1_1,int0)) & fact(stadt__1_1,real)) & gener(stadt__1_1,ge)) & quant(stadt__1_1,one)) & refer(stadt__1_1,refer_c)) & varia(stadt__1_1,varia_c)) & sort(london_0,fe)) & sort(c699,ent)) & card(c699,card_c)) & etype(c699,etype_c)) & fact(c699,real)) & gener(c699,gener_c)) & quant(c699,quant_c)) & refer(c699,refer_c)) & varia(c699,varia_c)) & sort(gro__337m__374tig_1_1,nq)),
% 1.30/0.68 input).
% 1.30/0.68 fof('$inc_sub__sub_0_expansion_$sk', plain, ((subr($sk6(X1,X2),sub_0) & (arg2($sk6(X1,X2),X2) & arg1($sk6(X1,X2),X1))) | ~sub(X1,X2)),
% 1.30/0.68 inference(negpush_and_skolemize,[],['$inc_sub__sub_0_expansion'])).
% 1.30/0.68 fof('$inc_sub__sub_0_expansion', axiom, (! [X0,X1] : (sub(X0,X1) => (? [X2] : ((arg1(X2,X0) & arg2(X2,X1)) & subr(X2,sub_0))))),
% 1.30/0.68 input).
% 1.30/0.68 fof('$inc_sub__bezeichnen_1_1_als_$sk', plain, ((subs($sk9(X1,X2,X3),bezeichnen_1_1) & (subr($sk7(X1,X2,X3),rprs_0) & (sub($sk8(X1,X2,X3),X3) & (obj($sk9(X1,X2,X3),X1) & (mcont($sk9(X1,X2,X3),$sk7(X1,X2,X3)) & (hsit(X2,$sk9(X1,X2,X3)) & (arg2($sk7(X1,X2,X3),$sk8(X1,X2,X3)) & arg1($sk7(X1,X2,X3),X1)))))))) | (~subr(X2,sub_0) | (~arg2(X2,X3) | ~arg1(X2,X1)))),
% 1.30/0.68 inference(negpush_and_skolemize,[],['$inc_sub__bezeichnen_1_1_als'])).
% 1.30/0.68 fof('$inc_sub__bezeichnen_1_1_als', axiom, (! [X0,X1,X2] : (((arg1(X0,X1) & arg2(X0,X2)) & subr(X0,sub_0)) => (? [X3,X4,X5] : (((((((arg1(X4,X1) & arg2(X4,X5)) & hsit(X0,X3)) & mcont(X3,X4)) & obj(X3,X1)) & sub(X5,X2)) & subr(X4,rprs_0)) & subs(X3,bezeichnen_1_1))))),
% 1.30/0.68 input).
% 1.30/0.68 cnf('1', plain, (~val(X,bmw_0) | ~val(Y,bmw_0) | ~attr(Z,Y) | ~attr(U,V) | ~attr(W,X) | ~obj(X2006,W) | ~sub(W,firma_1_1) | ~sub(X,name_1_1) | ~sub(Y,name_1_1)),
% 1.30/0.68 inference(cnf_transformation,[],['synth_qa07_007_mira_news_1253_$sk'])).
% 1.30/0.68 cnf('2', plain, (~val(X,bmw_0) | ~attr(Y,X) | ~attr(Z,U) | ~attr(V,X) | ~obj(W,Y) | ~sub(Y,firma_1_1) | ~sub(X,name_1_1)),
% 1.30/0.68 inference(factorization,[],['1'])).
% 1.30/0.68 cnf('3', plain, (val(c558,bmw_0)),
% 1.30/0.68 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1253_$sk'])).
% 1.30/0.68 cnf('4', plain, (sub(c558,name_1_1)),
% 1.30/0.68 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1253_$sk'])).
% 1.30/0.68 cnf('5', plain, (~attr(X,c558) | ~attr(Y,Z) | ~attr(U,c558) | ~obj(V,U) | ~sub(U,firma_1_1)),
% 1.30/0.68 inference(resolution,[then_simplify],['2','3','4'])).
% 1.30/0.68 cnf('6', plain, (~attr(X,c558) | ~attr(Y,Z) | ~obj(U,X) | ~sub(X,firma_1_1)),
% 1.30/0.68 inference(factorization,[],['5'])).
% 1.30/0.68 cnf('7', plain, (~attr(X,c558) | ~obj(Y,X) | ~sub(X,firma_1_1)),
% 1.30/0.68 inference(factorization,[],['6'])).
% 1.30/0.68 cnf('8', plain, (attr(c557,c558)),
% 1.30/0.68 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1253_$sk'])).
% 1.30/0.68 cnf('9', plain, (sub(c557,firma_1_1)),
% 1.30/0.68 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1253_$sk'])).
% 1.30/0.68 cnf('10', plain, (~obj(X,c557)),
% 1.30/0.68 inference(resolution,[then_simplify],['7','8','9'])).
% 1.30/0.68 cnf('11', plain, (sub(c557,firma_1_1)),
% 1.30/0.68 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1253_$sk'])).
% 1.30/0.68 cnf('12', plain, (arg2($sk6(X,Y),Y) | ~sub(X,Y)),
% 1.30/0.68 inference(cnf_transformation,[],['$inc_sub__sub_0_expansion_$sk'])).
% 1.30/0.68 cnf('13', plain, (arg2($sk6(c557,firma_1_1),firma_1_1)),
% 1.30/0.68 inference(resolution,[],['11','12'])).
% 1.30/0.68 cnf('14', plain, (obj($sk9(X,Y,Z),X) | ~subr(Y,sub_0) | ~arg1(Y,X) | ~arg2(Y,Z)),
% 1.30/0.68 inference(cnf_transformation,[],['$inc_sub__bezeichnen_1_1_als_$sk'])).
% 1.30/0.68 cnf('15', plain, (subr($sk6(X,Y),sub_0) | ~sub(X,Y)),
% 1.30/0.68 inference(cnf_transformation,[],['$inc_sub__sub_0_expansion_$sk'])).
% 1.30/0.68 cnf('16', plain, (subr($sk6(c557,firma_1_1),sub_0)),
% 1.30/0.68 inference(resolution,[],['11','15'])).
% 1.30/0.68 cnf('17', plain, (obj($sk9(X,$sk6(c557,firma_1_1),firma_1_1),X) | ~arg1($sk6(c557,firma_1_1),X)),
% 1.30/0.68 inference(resolution,[then_simplify],['13','14','16'])).
% 1.30/0.68 cnf('18', plain, (arg1($sk6(X,Y),X) | ~sub(X,Y)),
% 1.30/0.68 inference(cnf_transformation,[],['$inc_sub__sub_0_expansion_$sk'])).
% 1.30/0.68 cnf('19', plain, (arg1($sk6(c557,firma_1_1),c557)),
% 1.30/0.68 inference(resolution,[],['11','18'])).
% 1.30/0.68 cnf('20', plain, ($false),
% 1.30/0.68 inference(resolution,[then_simplify],['10','17','19'])).
% 1.30/0.68
% 1.30/0.68 % SZS output end CNFRefutation for /export/starexec/sandbox/benchmark/theBenchmark.p
% 1.30/0.68
% 1.30/0.68 run 1 fork 0 statistics:
% 1.30/0.68 ----------------------------------
% 1.30/0.68 this run seconds: 0.045100
% 1.30/0.68 total seconds: 0.108120
% 1.30/0.68 stat_given_used: 1181
% 1.30/0.68 stat_given_used_at_endgame: 0
% 1.30/0.68 stat_given_candidates: 1425
% 1.30/0.68 stat_given_candidates_at_endgame: 0
% 1.30/0.68 stat_given_candidates_h: 0
% 1.30/0.68 stat_binres_derived_cl: 1867
% 1.30/0.68 stat_binres_derived_cl_h: 0
% 1.30/0.68 stat_factor_derived_cl: 24
% 1.30/0.68 stat_para_derived_cl: 0
% 1.30/0.68 stat_tautologies_discarded: 0
% 1.30/0.68 stat_forward_subsumed: 7
% 1.30/0.68 stat_derived_cut: 200
% 1.30/0.68 stat_derived_rewritten: 0
% 1.30/0.68 stat_weight_discarded_building: 0
% 1.30/0.68 stat_weight_discarded_cl: 0
% 1.30/0.68 stat_internlimit_discarded_cl: 0
% 1.30/0.68 stat_simplified: 0 simplified 0 derived 0 given
% 1.30/0.68 stat_kept_cl: 1883
% 1.30/0.68 stat_built_cl: 25033
% 1.30/0.68 stat_hyperres_partial_cl: 0
% 1.30/0.68 stat_made_rewriters: 0
% 1.30/0.68 stat_backward_subsumed: 0
% 1.30/0.68 stat_propagated_subsumed: 0
% 1.30/0.68 stat_clsubs_attempted: 1126
% 1.30/0.68 stat_clsubs_fact_groundunit_found: 219
% 1.30/0.68 stat_clsubs_rule_groundunit_found: 1
% 1.30/0.68 stat_clsubs_top_meta_attempted: 274911
% 1.30/0.68 stat_clsubs_top_meta_failed: 273785
% 1.30/0.68 stat_clsubs_top_meta_nonpref_attempted: 274911
% 1.30/0.68 stat_clsubs_top_meta_nonpref_succeeded: 166290
% 1.30/0.68 stat_clsubs_top_meta_pref_attempted: 166290
% 1.30/0.68 stat_clsubs_top_meta_pref1_succeeded: 7492
% 1.30/0.68 stat_clsubs_top_meta_pref2_succeeded: 1604
% 1.30/0.68 stat_clsubs_top_meta_pref3_succeeded: 1126
% 1.30/0.68 stat_clsubs_top_meta_pref_succeeded: 1126
% 1.30/0.68 stat_clsubs_meta_attempted: 1985
% 1.30/0.68 stat_clsubs_meta_failed: 737
% 1.30/0.68 stat_clsubs_predsymbs_attempted: 0
% 1.30/0.68 stat_clsubs_unit_attempted: 52
% 1.30/0.68 stat_clsubs_full_attempted: 1074
% 1.30/0.68 stat_forwardsubs_attempted: 1891
% 1.30/0.68 stat_lit_hash_added: 22209
% 1.30/0.68 stat_lit_hash_computed: 37970
% 1.30/0.68 stat_lit_hash_match_found: 435
% 1.30/0.68 stat_lit_hash_match_miss: 22891
% 1.30/0.68 stat_lit_hash_cut_ok: 208
% 1.30/0.68 stat_lit_strong_cut_ok: 1
% 1.30/0.68 stat_lit_hash_subsume_ok: 7
% 1.30/0.68 clqueue els 10000000 used 1
% 1.30/0.68 clactive els 10000000 used 11576
% 1.30/0.68 clactivesubsume els 10000000 used 4411
% 1.30/0.68 queue_termbuf els 200000000 used 104630
% 1.30/0.68 hyper_termbuf els 100000000 used 1
% 1.30/0.68 active_termbuf els 100000000 used 112634
% 1.30/0.68 varstack els 5000 last used 1
% 1.30/0.68 given_termbuf els 10000000 last used 1
% 1.30/0.68 simplified_termbuf els 10000000 last used 1
% 1.30/0.68 derived_termbuf els 10000000 last used 29
% 1.30/0.68 wr_mallocs: 126540
% 1.30/0.68 wr_callocs: 21
% 1.30/0.68 wr_reallocs: 532
% 1.30/0.68 wr_frees: 2
% 1.30/0.68 wr_malloc_bytes: 4166974532
% 1.30/0.68 wr_calloc_bytes: 112065536
% 1.30/0.68 wr_realloc_bytes: 731976
% 1.30/0.68 wr_realloc_freebytes: 0
% 1.30/0.68 ----------------------------------
%------------------------------------------------------------------------------