TSTP Solution File: CSR115+10 by GKC---0.8
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- Process Solution
%------------------------------------------------------------------------------
% File : GKC---0.8
% Problem : CSR115+10 : TPTP v8.1.2. Released v4.0.0.
% Transfm : none
% Format : tptp:raw
% Command : gkc %s
% Computer : n011.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 21:24:21 EDT 2023
% Result : Theorem 0.20s 0.63s
% Output : CNFRefutation 0.20s
% Verified :
% SZS Type : -
% Comments :
%------------------------------------------------------------------------------
%----WARNING: Could not form TPTP format derivation
%------------------------------------------------------------------------------
%----ORIGINAL SYSTEM OUTPUT
% 0.07/0.12 % Problem : CSR115+10 : TPTP v8.1.2. Released v4.0.0.
% 0.07/0.13 % Command : gkc %s
% 0.13/0.34 % Computer : n011.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 12:55:10 EDT 2023
% 0.13/0.34 % CPUTime :
% 0.20/0.51
% 0.20/0.51 input clause set summed statistics:
% 0.20/0.51 ----------------------------------
% 0.20/0.51 in_clause_count: 10641
% 0.20/0.51 in_rule_clause_count: 338
% 0.20/0.51 in_fact_clause_count: 10303
% 0.20/0.51 in_answer_clause_count: 0
% 0.20/0.51 in_ground_clause_count: 10305
% 0.20/0.51 in_unit_clause_count: 10307
% 0.20/0.51 in_horn_clause_count: 10631
% 0.20/0.51 in_pos_clause_count: 10311
% 0.20/0.51 in_neg_clause_count: 11
% 0.20/0.51 in_poseq_clause_count: 0
% 0.20/0.51 in_negeq_clause_count: 0
% 0.20/0.51 in_unitposeq_clause_count: 0
% 0.20/0.51 in_chain_clause_count: 0
% 0.20/0.51 in_min_length: 1
% 0.20/0.51 in_max_length: 9
% 0.20/0.51 in_min_depth: 1
% 0.20/0.51 in_max_depth: 5
% 0.20/0.51 in_min_size: 3
% 0.20/0.51 in_max_size: 30
% 0.20/0.51 in_min_vars: 0
% 0.20/0.51 in_max_vars: 7
% 0.20/0.51 in_extaxiom_count: 10394
% 0.20/0.51 in_axiom_count: 0
% 0.20/0.51 in_assumption_count: 246
% 0.20/0.51 in_goal_count: 1
% 0.20/0.51 in_neg_goal_count: 1
% 0.20/0.51 in_pos_goal_count: 0
% 0.20/0.51 in_posunit_goal_count: 0
% 0.20/0.51
% 0.20/0.51 auto guide:
% 0.20/0.51 -----------
% 0.20/0.51 {
% 0.20/0.51 "print":1,
% 0.20/0.51 "print_level": 15,
% 0.20/0.51 "max_size": 0,
% 0.20/0.51 "max_depth": 0,
% 0.20/0.51 "max_length": 0,
% 0.20/0.51 "max_dseconds": 0,
% 0.20/0.51 "equality":0,
% 0.20/0.51 "runs":[
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0, "sine":5},
% 0.20/0.51 {"max_dseconds":1, "strategy":["hardness_pref"], "query_preference":0, "sine":5},
% 0.20/0.51 {"max_dseconds":1, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":1, "strategy":["hardness_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus", "positive_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus", "max_ground_weight"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "weight_select_ratio":100, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus", "double"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0, "sine":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["hardness_pref"], "query_preference":0, "weight_select_ratio":20, "depth_penalty":50, "length_penalty":100},
% 0.20/0.51 {"max_dseconds":1, "strategy":["hardness_pref", "max_ground_weight"], "query_preference":0},
% 0.20/0.51 {"length_penalty":100, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":1},
% 0.20/0.51 {"strategy":["hardness_pref", "max_weight"], "length_penalty":100, "depth_penalty":50, "max_depth":3, "var_weight":10, "repeat_var_weight":10, "max_dseconds":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["positive_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1, "depth_penalty":100},
% 0.20/0.51 {"var_weight":70, "repeat_var_weight":70, "max_depth":3, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["unit"], "query_preference":1, "reverse_clauselist":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":3},
% 0.20/0.51 {"max_dseconds":1, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":1, "strategy":["negative_pref"], "query_preference":0, "weight_select_ratio":100, "depth_penalty":100, "length_penalty":100},
% 0.20/0.51 {"max_dseconds":1, "strategy":["unit"], "query_preference":0, "var_weight":1, "depth_penalty":100, "repeat_var_weight":1},
% 0.20/0.51 {"weight_select_ratio":100, "length_penalty":100, "query_preference":1, "strategy":["query_focus"], "max_dseconds":1},
% 0.20/0.51
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0, "sine":5},
% 0.20/0.51 {"max_dseconds":10, "strategy":["hardness_pref"], "query_preference":0, "sine":5},
% 0.20/0.51 {"max_dseconds":10, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":10, "strategy":["hardness_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus", "positive_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus", "max_ground_weight"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "weight_select_ratio":100, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus", "double"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0, "sine":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["hardness_pref"], "query_preference":0, "weight_select_ratio":20, "depth_penalty":50, "length_penalty":100},
% 0.20/0.51 {"max_dseconds":10, "strategy":["hardness_pref", "max_ground_weight"], "query_preference":0},
% 0.20/0.51 {"length_penalty":100, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":10},
% 0.20/0.51 {"strategy":["hardness_pref", "max_weight"], "length_penalty":100, "depth_penalty":50, "max_depth":3, "var_weight":10, "repeat_var_weight":10, "max_dseconds":10},
% 0.20/0.51 {"max_dseconds":10, "strategy":["positive_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1, "depth_penalty":100},
% 0.20/0.51 {"var_weight":70, "repeat_var_weight":70, "max_depth":3, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":10},
% 0.20/0.51 {"max_dseconds":10, "strategy":["unit"], "query_preference":1, "reverse_clauselist":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":3},
% 0.20/0.51 {"max_dseconds":10, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":10, "strategy":["negative_pref"], "query_preference":0, "weight_select_ratio":100, "depth_penalty":100, "length_penalty":100},
% 0.20/0.51 {"max_dseconds":10, "strategy":["unit"], "query_preference":0, "var_weight":1, "depth_penalty":100, "repeat_var_weight":1},
% 0.20/0.51 {"weight_select_ratio":100, "length_penalty":100, "query_preference":1, "strategy":["query_focus"], "max_dseconds":10},
% 0.20/0.51
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":50, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":50, "strategy":["hardness_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus", "positive_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus", "max_ground_weight"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "weight_select_ratio":100, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus", "double"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":0, "sine":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["hardness_pref"], "query_preference":0, "weight_select_ratio":20, "depth_penalty":50, "length_penalty":100},
% 0.20/0.51 {"max_dseconds":50, "strategy":["hardness_pref", "max_ground_weight"], "query_preference":0},
% 0.20/0.51 {"length_penalty":100, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":50},
% 0.20/0.51 {"strategy":["hardness_pref", "max_weight"], "length_penalty":100, "depth_penalty":50, "max_depth":3, "var_weight":10, "repeat_var_weight":10, "max_dseconds":50},
% 0.20/0.51 {"max_dseconds":50, "strategy":["positive_pref"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1, "depth_penalty":100},
% 0.20/0.51 {"var_weight":70, "repeat_var_weight":70, "max_depth":3, "query_preference":0, "strategy":["negative_pref"], "max_dseconds":50},
% 0.20/0.51 {"max_dseconds":50, "strategy":["unit"], "query_preference":1, "reverse_clauselist":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":3},
% 0.20/0.51 {"max_dseconds":50, "strategy":["query_focus"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":1, "var_weight":1, "repeat_var_weight":1},
% 0.20/0.51 {"max_dseconds":50, "strategy":["negative_pref"], "query_preference":0, "weight_select_ratio":100, "depth_penalty":100, "length_penalty":100},
% 0.20/0.51 {"max_dseconds":50, "strategy":["unit"], "query_preference":0, "var_weight":1, "depth_penalty":100, "repeat_var_weight":1},
% 0.20/0.51 {"weight_select_ratio":100, "length_penalty":100, "query_preference":1, "strategy":["query_focus"], "max_dseconds":50},
% 0.20/0.51
% 0.20/0.51 {"max_dseconds":250, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":250, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":250, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.51 {"max_dseconds":250, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":250, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.51 {"max_dseconds":250, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":250, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":250, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2},
% 0.20/0.51
% 0.20/0.51 {"max_dseconds":1250, "strategy":["query_focus", "unit"], "query_preference":0},
% 0.20/0.51 {"max_dseconds":1250, "strategy":["query_focus", "unit"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1250, "strategy":["query_focus", "unit"], "query_preference":1, "sine":1},
% 0.20/0.51 {"max_dseconds":1250, "strategy":["query_focus"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1250, "strategy":["negative_pref"], "query_preference":1, "sine":2},
% 0.20/0.51 {"max_dseconds":1250, "strategy":["query_focus", "positive_pref"], "query_preference":1},
% 0.20/0.51 {"max_dseconds":1250, "strategy":["unit"], "query_preference":0, "sine":2},
% 0.20/0.51 {"max_dseconds":1250, "strategy":["unit", "posunitpara"], "query_preference":0, "sine":2}
% 0.20/0.51
% 0.20/0.51 ]}
% 0.20/0.51
% 0.20/0.51
% 0.20/0.51 **** run 1 fork 0 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":0}
% 0.20/0.51
% 0.20/0.51 **** run 2 fork 1 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":1}
% 0.20/0.51
% 0.20/0.51 **** run 3 fork 2 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":1,"sine":1}
% 0.20/0.51
% 0.20/0.51 **** run 4 fork 3 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["query_focus"],"query_preference":1}
% 0.20/0.51
% 0.20/0.51 **** run 5 fork 4 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["negative_pref"],"query_preference":1,"sine":2}
% 0.20/0.51
% 0.20/0.51 **** run 6 fork 5 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["query_focus","positive_pref"],"query_preference":1}
% 0.20/0.51
% 0.20/0.51 **** run 8 fork 7 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["negative_pref"],"query_preference":0,"sine":5}
% 0.20/0.51
% 0.20/0.51 **** run 7 fork 6 starts with strategy
% 0.20/0.51 {"max_dseconds":1,"strategy":["unit"],"query_preference":0,"sine":2}
% 0.20/0.63
% 0.20/0.63
% 0.20/0.63 result: proof found
% 0.20/0.63 for /export/starexec/sandbox2/benchmark/theBenchmark.p
% 0.20/0.63 by run 1 fork 0 strategy {"max_dseconds":1,"strategy":["query_focus","unit"],"query_preference":0}
% 0.20/0.63 % SZS status Theorem for /export/starexec/sandbox2/benchmark/theBenchmark.p
% 0.20/0.63
% 0.20/0.63 % SZS output start CNFRefutation for /export/starexec/sandbox2/benchmark/theBenchmark.p
% 0.20/0.63 fof('synth_qa07_007_mira_news_1108_$sk', plain, (~val(X7,bmw_0) | (~val(X1,bmw_0) | (~sub(X7,name_1_1) | (~sub(X2,firma_1_1) | (~sub(X1,name_1_1) | (~obj(X3,X2) | (~attr(X6,X5) | (~attr(X4,X7) | ~attr(X2,X1))))))))),
% 0.20/0.63 inference(negpush_and_skolemize,[],['synth_qa07_007_mira_news_1108'])).
% 0.20/0.63 fof('synth_qa07_007_mira_news_1108', conjecture, (? [X0,X1,X2,X3,X4,X5,X6] : ((((((((attr(X0,X1) & attr(X3,X2)) & attr(X5,X6)) & obj(X4,X0)) & sub(X1,name_1_1)) & sub(X0,firma_1_1)) & sub(X2,name_1_1)) & val(X1,bmw_0)) & val(X2,bmw_0))),
% 0.20/0.63 input).
% 0.20/0.63 fof('ave07_era5_synth_qa07_007_mira_news_1108_$sk', plain, (varia(analogie__1_1,varia_c) & (refer(analogie__1_1,refer_c) & (quant(analogie__1_1,one) & (gener(analogie__1_1,ge) & (fact(analogie__1_1,real) & (etype(analogie__1_1,int0) & (card(analogie__1_1,int1) & (sort(analogie__1_1,io) & (sort(marken_0,fe) & (varia(c59878,varia_c) & (refer(c59878,refer_c) & (quant(c59878,quant_c) & (gener(c59878,gener_c) & (fact(c59878,real) & (etype(c59878,etype_c) & (card(c59878,card_c) & (sort(c59878,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(c59036,varia_c) & (refer(c59036,indet) & (quant(c59036,one) & (gener(c59036,sp) & (fact(c59036,real) & (etype(c59036,int0) & (card(c59036,int1) & (sort(c59036,na) & (varia(c59035,con) & (refer(c59035,det) & (quant(c59035,one) & (gener(c59035,sp) & (fact(c59035,real) & (etype(c59035,int0) & (card(c59035,int1) & (sort(c59035,io) & (sort(c59035,d) & (varia(markenidentit__344t_1_1,varia_c) & (refer(markenidentit__344t_1_1,refer_c) & (quant(markenidentit__344t_1_1,one) & (gener(markenidentit__344t_1_1,ge) & (fact(markenidentit__344t_1_1,real) & (etype(markenidentit__344t_1_1,int0) & (card(markenidentit__344t_1_1,int1) & (sort(markenidentit__344t_1_1,io) & (sort(eigen_1_1,nq) & (varia(c58978,varia_c) & (refer(c58978,refer_c) & (quant(c58978,one) & (gener(c58978,gener_c) & (fact(c58978,real) & (etype(c58978,int0) & (card(c58978,int1) & (sort(c58978,io) & (sort(britisch__1_1,nq) & (varia(c58970,varia_c) & (refer(c58970,refer_c) & (quant(c58970,one) & (gener(c58970,gener_c) & (fact(c58970,real) & (etype(c58970,int0) & (card(c58970,int1) & (sort(c58970,io) & (sort(c58970,d) & (sort(rover_0,fe) & (varia(c58968,varia_c) & (refer(c58968,indet) & (quant(c58968,one) & (gener(c58968,sp) & (fact(c58968,real) & (etype(c58968,int0) & (card(c58968,int1) & (sort(c58968,na) & (varia(c58967,con) & (refer(c58967,det) & (quant(c58967,one) & (gener(c58967,sp) & (fact(c58967,real) & (etype(c58967,int0) & (card(c58967,int1) & (sort(c58967,io) & (sort(c58967,d) & (varia(vorzeitigkeit_1_1,varia_c) & (refer(vorzeitigkeit_1_1,refer_c) & (quant(vorzeitigkeit_1_1,one) & (gener(vorzeitigkeit_1_1,ge) & (fact(vorzeitigkeit_1_1,real) & (etype(vorzeitigkeit_1_1,int0) & (card(vorzeitigkeit_1_1,int1) & (sort(vorzeitigkeit_1_1,ta) & (varia(c57309,varia_c) & (refer(c57309,refer_c) & (quant(c57309,one) & (gener(c57309,gener_c) & (fact(c57309,real) & (etype(c57309,int0) & (card(c57309,int1) & (sort(c57309,ta) & (sort(langfristig_1_1,tq) & (varia(bem__374hen_3_1,varia_c) & (refer(bem__374hen_3_1,refer_c) & (quant(bem__374hen_3_1,one) & (gener(bem__374hen_3_1,ge) & (fact(bem__374hen_3_1,real) & (etype(bem__374hen_3_1,int0) & (card(bem__374hen_3_1,int1) & (sort(bem__374hen_3_1,ad) & (varia(c57299,varia_c) & (refer(c57299,refer_c) & (quant(c57299,mult) & (gener(c57299,gener_c) & (fact(c57299,real) & (etype(c57299,int1) & (card(c57299,cons(x_constant,cons(int1,nil))) & (sort(c57299,ad) & (varia(rover_1_1,varia_c) & (refer(rover_1_1,refer_c) & (quant(rover_1_1,one) & (gener(rover_1_1,ge) & (fact(rover_1_1,real) & (etype(rover_1_1,int0) & (card(rover_1_1,int1) & (sort(rover_1_1,d) & (varia(c57295,varia_c) & (refer(c57295,indet) & (quant(c57295,mult) & (gener(c57295,gener_c) & (fact(c57295,real) & (etype(c57295,int1) & (card(c57295,cons(x_constant,cons(int1,nil))) & (sort(c57295,d) & (sort(honda_0,fe) & (varia(c59030,varia_c) & (refer(c59030,indet) & (quant(c59030,one) & (gener(c59030,sp) & (fact(c59030,real) & (etype(c59030,int0) & (card(c59030,int1) & (sort(c59030,na) & (varia(c57289,varia_c) & (refer(c57289,indet) & (quant(c57289,one) & (gener(c57289,sp) & (fact(c57289,real) & (etype(c57289,int0) & (card(c57289,int1) & (sort(c57289,na) & (varia(c57288,con) & (refer(c57288,det) & (quant(c57288,one) & (gener(c57288,sp) & (fact(c57288,real) & (etype(c57288,int0) & (card(c57288,int1) & (sort(c57288,io) & (sort(c57288,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(c57202,varia_c) & (refer(c57202,indet) & (quant(c57202,one) & (gener(c57202,sp) & (fact(c57202,real) & (etype(c57202,int0) & (card(c57202,int1) & (sort(c57202,na) & (varia(c57201,con) & (refer(c57201,det) & (quant(c57201,one) & (gener(c57201,sp) & (fact(c57201,real) & (etype(c57201,int0) & (card(c57201,int1) & (sort(c57201,io) & (sort(c57201,d) & (varia(einigung_1_1,varia_c) & (refer(einigung_1_1,refer_c) & (quant(einigung_1_1,one) & (gener(einigung_1_1,ge) & (fact(einigung_1_1,real) & (etype(einigung_1_1,int0) & (card(einigung_1_1,int1) & (sort(einigung_1_1,ad) & (varia(c57187,con) & (refer(c57187,det) & (quant(c57187,one) & (gener(c57187,sp) & (fact(c57187,real) & (etype(c57187,int0) & (card(c57187,int1) & (sort(c57187,ad) & (sub(markenidentit__344t_1_1,analogie__1_1) & (assoc(markenidentit__344t_1_1,marken_0) & (tupl_p12(c59878,c57187,c57201,c57288,c57295,c57299,c57309,c58967,c58970,c58978,c57288,c59035) & (val(c59036,london_0) & (sub(c59036,name_1_1) & (sub(c59035,stadt__1_1) & (attr(c59035,c59036) & (val(c59030,honda_0) & (sub(c59030,name_1_1) & (sub(c58978,markenidentit__344t_1_1) & (prop(c58978,eigen_1_1) & (sub(c58970,firma_1_1) & (prop(c58970,britisch__1_1) & (val(c58968,rover_0) & (sub(c58968,name_1_1) & (sub(c58967,firma_1_1) & (attr(c58967,c58968) & (sub(c57309,vorzeitigkeit_1_1) & (prop(c57299,langfristig_1_1) & (preds(c57299,bem__374hen_3_1) & (pred(c57295,rover_1_1) & (val(c57289,honda_0) & (sub(c57289,name_1_1) & (sub(c57288,firma_1_1) & (attr(c57288,c59030) & (attr(c57288,c57289) & (val(c57202,bmw_0) & (sub(c57202,name_1_1) & (sub(c57201,firma_1_1) & (attr(c57201,c57202) & subs(c57187,einigung_1_1)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))),
% 0.20/0.63 inference(negpush_and_skolemize,[],['ave07_era5_synth_qa07_007_mira_news_1108'])).
% 0.20/0.63 fof('ave07_era5_synth_qa07_007_mira_news_1108', hypothesis, (((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((subs(c57187,einigung_1_1) & attr(c57201,c57202)) & sub(c57201,firma_1_1)) & sub(c57202,name_1_1)) & val(c57202,bmw_0)) & attr(c57288,c57289)) & attr(c57288,c59030)) & sub(c57288,firma_1_1)) & sub(c57289,name_1_1)) & val(c57289,honda_0)) & pred(c57295,rover_1_1)) & preds(c57299,bem__374hen_3_1)) & prop(c57299,langfristig_1_1)) & sub(c57309,vorzeitigkeit_1_1)) & attr(c58967,c58968)) & sub(c58967,firma_1_1)) & sub(c58968,name_1_1)) & val(c58968,rover_0)) & prop(c58970,britisch__1_1)) & sub(c58970,firma_1_1)) & prop(c58978,eigen_1_1)) & sub(c58978,markenidentit__344t_1_1)) & sub(c59030,name_1_1)) & val(c59030,honda_0)) & attr(c59035,c59036)) & sub(c59035,stadt__1_1)) & sub(c59036,name_1_1)) & val(c59036,london_0)) & tupl_p12(c59878,c57187,c57201,c57288,c57295,c57299,c57309,c58967,c58970,c58978,c57288,c59035)) & assoc(markenidentit__344t_1_1,marken_0)) & sub(markenidentit__344t_1_1,analogie__1_1)) & sort(c57187,ad)) & card(c57187,int1)) & etype(c57187,int0)) & fact(c57187,real)) & gener(c57187,sp)) & quant(c57187,one)) & refer(c57187,det)) & varia(c57187,con)) & sort(einigung_1_1,ad)) & card(einigung_1_1,int1)) & etype(einigung_1_1,int0)) & fact(einigung_1_1,real)) & gener(einigung_1_1,ge)) & quant(einigung_1_1,one)) & refer(einigung_1_1,refer_c)) & varia(einigung_1_1,varia_c)) & sort(c57201,d)) & sort(c57201,io)) & card(c57201,int1)) & etype(c57201,int0)) & fact(c57201,real)) & gener(c57201,sp)) & quant(c57201,one)) & refer(c57201,det)) & varia(c57201,con)) & sort(c57202,na)) & card(c57202,int1)) & etype(c57202,int0)) & fact(c57202,real)) & gener(c57202,sp)) & quant(c57202,one)) & refer(c57202,indet)) & varia(c57202,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(c57288,d)) & sort(c57288,io)) & card(c57288,int1)) & etype(c57288,int0)) & fact(c57288,real)) & gener(c57288,sp)) & quant(c57288,one)) & refer(c57288,det)) & varia(c57288,con)) & sort(c57289,na)) & card(c57289,int1)) & etype(c57289,int0)) & fact(c57289,real)) & gener(c57289,sp)) & quant(c57289,one)) & refer(c57289,indet)) & varia(c57289,varia_c)) & sort(c59030,na)) & card(c59030,int1)) & etype(c59030,int0)) & fact(c59030,real)) & gener(c59030,sp)) & quant(c59030,one)) & refer(c59030,indet)) & varia(c59030,varia_c)) & sort(honda_0,fe)) & sort(c57295,d)) & card(c57295,cons(x_constant,cons(int1,nil)))) & etype(c57295,int1)) & fact(c57295,real)) & gener(c57295,gener_c)) & quant(c57295,mult)) & refer(c57295,indet)) & varia(c57295,varia_c)) & sort(rover_1_1,d)) & card(rover_1_1,int1)) & etype(rover_1_1,int0)) & fact(rover_1_1,real)) & gener(rover_1_1,ge)) & quant(rover_1_1,one)) & refer(rover_1_1,refer_c)) & varia(rover_1_1,varia_c)) & sort(c57299,ad)) & card(c57299,cons(x_constant,cons(int1,nil)))) & etype(c57299,int1)) & fact(c57299,real)) & gener(c57299,gener_c)) & quant(c57299,mult)) & refer(c57299,refer_c)) & varia(c57299,varia_c)) & sort(bem__374hen_3_1,ad)) & card(bem__374hen_3_1,int1)) & etype(bem__374hen_3_1,int0)) & fact(bem__374hen_3_1,real)) & gener(bem__374hen_3_1,ge)) & quant(bem__374hen_3_1,one)) & refer(bem__374hen_3_1,refer_c)) & varia(bem__374hen_3_1,varia_c)) & sort(langfristig_1_1,tq)) & sort(c57309,ta)) & card(c57309,int1)) & etype(c57309,int0)) & fact(c57309,real)) & gener(c57309,gener_c)) & quant(c57309,one)) & refer(c57309,refer_c)) & varia(c57309,varia_c)) & sort(vorzeitigkeit_1_1,ta)) & card(vorzeitigkeit_1_1,int1)) & etype(vorzeitigkeit_1_1,int0)) & fact(vorzeitigkeit_1_1,real)) & gener(vorzeitigkeit_1_1,ge)) & quant(vorzeitigkeit_1_1,one)) & refer(vorzeitigkeit_1_1,refer_c)) & varia(vorzeitigkeit_1_1,varia_c)) & sort(c58967,d)) & sort(c58967,io)) & card(c58967,int1)) & etype(c58967,int0)) & fact(c58967,real)) & gener(c58967,sp)) & quant(c58967,one)) & refer(c58967,det)) & varia(c58967,con)) & sort(c58968,na)) & card(c58968,int1)) & etype(c58968,int0)) & fact(c58968,real)) & gener(c58968,sp)) & quant(c58968,one)) & refer(c58968,indet)) & varia(c58968,varia_c)) & sort(rover_0,fe)) & sort(c58970,d)) & sort(c58970,io)) & card(c58970,int1)) & etype(c58970,int0)) & fact(c58970,real)) & gener(c58970,gener_c)) & quant(c58970,one)) & refer(c58970,refer_c)) & varia(c58970,varia_c)) & sort(britisch__1_1,nq)) & sort(c58978,io)) & card(c58978,int1)) & etype(c58978,int0)) & fact(c58978,real)) & gener(c58978,gener_c)) & quant(c58978,one)) & refer(c58978,refer_c)) & varia(c58978,varia_c)) & sort(eigen_1_1,nq)) & sort(markenidentit__344t_1_1,io)) & card(markenidentit__344t_1_1,int1)) & etype(markenidentit__344t_1_1,int0)) & fact(markenidentit__344t_1_1,real)) & gener(markenidentit__344t_1_1,ge)) & quant(markenidentit__344t_1_1,one)) & refer(markenidentit__344t_1_1,refer_c)) & varia(markenidentit__344t_1_1,varia_c)) & sort(c59035,d)) & sort(c59035,io)) & card(c59035,int1)) & etype(c59035,int0)) & fact(c59035,real)) & gener(c59035,sp)) & quant(c59035,one)) & refer(c59035,det)) & varia(c59035,con)) & sort(c59036,na)) & card(c59036,int1)) & etype(c59036,int0)) & fact(c59036,real)) & gener(c59036,sp)) & quant(c59036,one)) & refer(c59036,indet)) & varia(c59036,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(c59878,ent)) & card(c59878,card_c)) & etype(c59878,etype_c)) & fact(c59878,real)) & gener(c59878,gener_c)) & quant(c59878,quant_c)) & refer(c59878,refer_c)) & varia(c59878,varia_c)) & sort(marken_0,fe)) & sort(analogie__1_1,io)) & card(analogie__1_1,int1)) & etype(analogie__1_1,int0)) & fact(analogie__1_1,real)) & gener(analogie__1_1,ge)) & quant(analogie__1_1,one)) & refer(analogie__1_1,refer_c)) & varia(analogie__1_1,varia_c)),
% 0.20/0.63 input).
% 0.20/0.63 fof('$inc_sub__sub_0_expansion_$sk', plain, ((subr($sk6(X1,X2),sub_0) & (arg2($sk6(X1,X2),X2) & arg1($sk6(X1,X2),X1))) | ~sub(X1,X2)),
% 0.20/0.63 inference(negpush_and_skolemize,[],['$inc_sub__sub_0_expansion'])).
% 0.20/0.63 fof('$inc_sub__sub_0_expansion', axiom, (! [X0,X1] : (sub(X0,X1) => (? [X2] : ((arg1(X2,X0) & arg2(X2,X1)) & subr(X2,sub_0))))),
% 0.20/0.63 input).
% 0.20/0.63 fof('$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($sk7(X1,X2,X3),X1)))))))) | (~subr(X2,sub_0) | (~arg2(X2,X3) | ~arg1(X2,X1)))),
% 0.20/0.63 inference(negpush_and_skolemize,[],['$inc_sub__bezeichnen_1_1_als'])).
% 0.20/0.63 fof('$inc_sub__bezeichnen_1_1_als', axiom, (! [X0,X1,X2] : (((arg1(X0,X1) & arg2(X0,X2)) & subr(X0,sub_0)) => (? [X3,X4,X5] : (((((((arg1(X4,X1) & arg2(X4,X5)) & hsit(X0,X3)) & mcont(X3,X4)) & obj(X3,X1)) & sub(X5,X2)) & subr(X4,rprs_0)) & subs(X3,bezeichnen_1_1))))),
% 0.20/0.63 input).
% 0.20/0.63 cnf('1', plain, (~val(X,bmw_0) | ~val(Y,bmw_0) | ~attr(Z,Y) | ~attr(U,V) | ~attr(W,X) | ~obj(X2006,W) | ~sub(W,firma_1_1) | ~sub(X,name_1_1) | ~sub(Y,name_1_1)),
% 0.20/0.63 inference(cnf_transformation,[],['synth_qa07_007_mira_news_1108_$sk'])).
% 0.20/0.63 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)),
% 0.20/0.63 inference(factorization,[],['1'])).
% 0.20/0.63 cnf('3', plain, (val(c57202,bmw_0)),
% 0.20/0.63 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1108_$sk'])).
% 0.20/0.63 cnf('4', plain, (sub(c57202,name_1_1)),
% 0.20/0.63 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1108_$sk'])).
% 0.20/0.63 cnf('5', plain, (~attr(X,c57202) | ~attr(Y,Z) | ~attr(U,c57202) | ~obj(V,U) | ~sub(U,firma_1_1)),
% 0.20/0.63 inference(resolution,[then_simplify],['2','3','4'])).
% 0.20/0.63 cnf('6', plain, (~attr(X,c57202) | ~attr(Y,Z) | ~obj(U,X) | ~sub(X,firma_1_1)),
% 0.20/0.63 inference(factorization,[],['5'])).
% 0.20/0.63 cnf('7', plain, (~attr(X,c57202) | ~obj(Y,X) | ~sub(X,firma_1_1)),
% 0.20/0.63 inference(factorization,[],['6'])).
% 0.20/0.63 cnf('8', plain, (attr(c57201,c57202)),
% 0.20/0.63 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1108_$sk'])).
% 0.20/0.63 cnf('9', plain, (sub(c57201,firma_1_1)),
% 0.20/0.63 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1108_$sk'])).
% 0.20/0.63 cnf('10', plain, (~obj(X,c57201)),
% 0.20/0.63 inference(resolution,[then_simplify],['7','8','9'])).
% 0.20/0.63 cnf('11', plain, (sub(c57201,firma_1_1)),
% 0.20/0.63 inference(cnf_transformation,[],['ave07_era5_synth_qa07_007_mira_news_1108_$sk'])).
% 0.20/0.63 cnf('12', plain, (arg2($sk6(X,Y),Y) | ~sub(X,Y)),
% 0.20/0.63 inference(cnf_transformation,[],['$inc_sub__sub_0_expansion_$sk'])).
% 0.20/0.63 cnf('13', plain, (arg2($sk6(c57201,firma_1_1),firma_1_1)),
% 0.20/0.63 inference(resolution,[],['11','12'])).
% 0.20/0.63 cnf('14', plain, (obj($sk9(X,Y,Z),X) | ~subr(Y,sub_0) | ~arg1(Y,X) | ~arg2(Y,Z)),
% 0.20/0.63 inference(cnf_transformation,[],['$inc_sub__bezeichnen_1_1_als_$sk'])).
% 0.20/0.63 cnf('15', plain, (subr($sk6(X,Y),sub_0) | ~sub(X,Y)),
% 0.20/0.63 inference(cnf_transformation,[],['$inc_sub__sub_0_expansion_$sk'])).
% 0.20/0.63 cnf('16', plain, (subr($sk6(c57201,firma_1_1),sub_0)),
% 0.20/0.63 inference(resolution,[],['11','15'])).
% 0.20/0.63 cnf('17', plain, (obj($sk9(X,$sk6(c57201,firma_1_1),firma_1_1),X) | ~arg1($sk6(c57201,firma_1_1),X)),
% 0.20/0.63 inference(resolution,[then_simplify],['13','14','16'])).
% 0.20/0.63 cnf('18', plain, (arg1($sk6(X,Y),X) | ~sub(X,Y)),
% 0.20/0.63 inference(cnf_transformation,[],['$inc_sub__sub_0_expansion_$sk'])).
% 0.20/0.63 cnf('19', plain, (arg1($sk6(c57201,firma_1_1),c57201)),
% 0.20/0.63 inference(resolution,[],['11','18'])).
% 0.20/0.63 cnf('20', plain, ($false),
% 0.20/0.63 inference(resolution,[then_simplify],['10','17','19'])).
% 0.20/0.63
% 0.20/0.63 % SZS output end CNFRefutation for /export/starexec/sandbox2/benchmark/theBenchmark.p
% 0.20/0.63
% 0.20/0.63 run 1 fork 0 statistics:
% 0.20/0.63 ----------------------------------
% 0.20/0.63 this run seconds: 0.057666
% 0.20/0.63 total seconds: 0.122014
% 0.20/0.63 stat_given_used: 1605
% 0.20/0.63 stat_given_used_at_endgame: 0
% 0.20/0.63 stat_given_candidates: 1946
% 0.20/0.63 stat_given_candidates_at_endgame: 0
% 0.20/0.63 stat_given_candidates_h: 0
% 0.20/0.63 stat_binres_derived_cl: 2537
% 0.20/0.63 stat_binres_derived_cl_h: 0
% 0.20/0.63 stat_factor_derived_cl: 28
% 0.20/0.63 stat_para_derived_cl: 0
% 0.20/0.63 stat_tautologies_discarded: 0
% 0.20/0.63 stat_forward_subsumed: 7
% 0.20/0.63 stat_derived_cut: 295
% 0.20/0.63 stat_derived_rewritten: 0
% 0.20/0.63 stat_weight_discarded_building: 0
% 0.20/0.63 stat_weight_discarded_cl: 0
% 0.20/0.63 stat_internlimit_discarded_cl: 0
% 0.20/0.63 stat_simplified: 2 simplified 0 derived 0 given
% 0.20/0.63 stat_kept_cl: 2557
% 0.20/0.63 stat_built_cl: 26557
% 0.20/0.63 stat_hyperres_partial_cl: 0
% 0.20/0.63 stat_made_rewriters: 0
% 0.20/0.63 stat_backward_subsumed: 0
% 0.20/0.63 stat_propagated_subsumed: 0
% 0.20/0.63 stat_clsubs_attempted: 2010
% 0.20/0.63 stat_clsubs_fact_groundunit_found: 291
% 0.20/0.63 stat_clsubs_rule_groundunit_found: 2
% 0.20/0.63 stat_clsubs_top_meta_attempted: 551695
% 0.20/0.63 stat_clsubs_top_meta_failed: 549685
% 0.20/0.63 stat_clsubs_top_meta_nonpref_attempted: 551695
% 0.20/0.63 stat_clsubs_top_meta_nonpref_succeeded: 323978
% 0.20/0.63 stat_clsubs_top_meta_pref_attempted: 323978
% 0.20/0.63 stat_clsubs_top_meta_pref1_succeeded: 17486
% 0.20/0.63 stat_clsubs_top_meta_pref2_succeeded: 2865
% 0.20/0.63 stat_clsubs_top_meta_pref3_succeeded: 2010
% 0.20/0.63 stat_clsubs_top_meta_pref_succeeded: 2010
% 0.20/0.63 stat_clsubs_meta_attempted: 3548
% 0.20/0.63 stat_clsubs_meta_failed: 1321
% 0.20/0.63 stat_clsubs_predsymbs_attempted: 0
% 0.20/0.63 stat_clsubs_unit_attempted: 67
% 0.20/0.63 stat_clsubs_full_attempted: 1943
% 0.20/0.63 stat_forwardsubs_attempted: 2565
% 0.20/0.63 stat_lit_hash_added: 22867
% 0.20/0.63 stat_lit_hash_computed: 44602
% 0.20/0.63 stat_lit_hash_match_found: 610
% 0.20/0.63 stat_lit_hash_match_miss: 31527
% 0.20/0.63 stat_lit_hash_cut_ok: 309
% 0.20/0.63 stat_lit_strong_cut_ok: 2
% 0.20/0.63 stat_lit_hash_subsume_ok: 7
% 0.20/0.63 clqueue els 10000000 used 1
% 0.20/0.63 clactive els 10000000 used 12000
% 0.20/0.63 clactivesubsume els 10000000 used 6241
% 0.20/0.63 queue_termbuf els 200000000 used 141773
% 0.20/0.63 hyper_termbuf els 100000000 used 1
% 0.20/0.63 active_termbuf els 100000000 used 123396
% 0.20/0.63 varstack els 5000 last used 1
% 0.20/0.63 given_termbuf els 10000000 last used 1
% 0.20/0.63 simplified_termbuf els 10000000 last used 1
% 0.20/0.63 derived_termbuf els 10000000 last used 29
% 0.20/0.63 wr_mallocs: 129931
% 0.20/0.63 wr_callocs: 21
% 0.20/0.63 wr_reallocs: 654
% 0.20/0.63 wr_frees: 2
% 0.20/0.63 wr_malloc_bytes: 4167090196
% 0.20/0.63 wr_calloc_bytes: 112065536
% 0.20/0.63 wr_realloc_bytes: 788784
% 0.20/0.63 wr_realloc_freebytes: 0
% 0.20/0.63 ----------------------------------
%------------------------------------------------------------------------------