F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.0661, 召回率: 0.0834, F1: 0.0738
BERT Score: 
- Precision: 0.6572
- Recall: 0.8299
- F1: 0.6880

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.1930, 召回率: 0.2188, F1: 0.2051
BERT Score: 
- Precision: 0.7579
- Recall: 0.8663
- F1: 0.7755

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.2203, 召回率: 0.2510, F1: 0.2346
BERT Score: 
- Precision: 0.7574
- Recall: 0.8720
- F1: 0.7767

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.1061, 召回率: 0.1275, F1: 0.1158
BERT Score: 
- Precision: 0.6904
- Recall: 0.8327
- F1: 0.7088

F:/GeoLLM/output/output_result/Task1/knn/one_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.2115, 召回率: 0.2438, F1: 0.2265
BERT Score: 
- Precision: 0.7573
- Recall: 0.8712
- F1: 0.7803

F:/GeoLLM/output/output_result/Task1/knn/two_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.2182, 召回率: 0.2589, F1: 0.2368
BERT Score: 
- Precision: 0.7407
- Recall: 0.8763
- F1: 0.7699

F:/GeoLLM/output/output_result/Task1/knn/three_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.2134, 召回率: 0.2576, F1: 0.2334
BERT Score: 
- Precision: 0.7443
- Recall: 0.8750
- F1: 0.7670

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/gpt-3p5-turbo.json: 
Triple Match: 
精确率: 0.0697, 召回率: 0.0834, F1: 0.0759
BERT Score: 
- Precision: 0.6656
- Recall: 0.8230
- F1: 0.6876

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1886, 召回率: 0.2208, F1: 0.2034
BERT Score: 
- Precision: 0.7485
- Recall: 0.8543
- F1: 0.7526

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.3610, 召回率: 0.3968, F1: 0.3781
BERT Score: 
- Precision: 0.8501
- Recall: 0.9099
- F1: 0.8592

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.3955, 召回率: 0.4251, F1: 0.4098
BERT Score: 
- Precision: 0.8668
- Recall: 0.9091
- F1: 0.8666

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2683, 召回率: 0.3029, F1: 0.2846
BERT Score: 
- Precision: 0.7899
- Recall: 0.8687
- F1: 0.7944

F:/GeoLLM/output/output_result/Task1/knn/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.3464, 召回率: 0.3765, F1: 0.3608
BERT Score: 
- Precision: 0.8483
- Recall: 0.9018
- F1: 0.8524

F:/GeoLLM/output/output_result/Task1/knn/two_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.4056, 召回率: 0.4376, F1: 0.4210
BERT Score: 
- Precision: 0.8624
- Recall: 0.9076
- F1: 0.8639

F:/GeoLLM/output/output_result/Task1/knn/three_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.4176, 召回率: 0.4514, F1: 0.4338
BERT Score: 
- Precision: 0.8741
- Recall: 0.9116
- F1: 0.8735

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1836, 召回率: 0.2050, F1: 0.1937
BERT Score: 
- Precision: 0.7454
- Recall: 0.8488
- F1: 0.7533

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.1582, 召回率: 0.2490, F1: 0.1935
BERT Score: 
- Precision: 0.6071
- Recall: 0.8016
- F1: 0.5745

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.3194, 召回率: 0.4310, F1: 0.3669
BERT Score: 
- Precision: 0.7712
- Recall: 0.9212
- F1: 0.8070

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.3390, 召回率: 0.4428, F1: 0.3840
BERT Score: 
- Precision: 0.7869
- Recall: 0.9324
- F1: 0.8267

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.2302, 召回率: 0.3338, F1: 0.2725
BERT Score: 
- Precision: 0.6866
- Recall: 0.8960
- F1: 0.7329

F:/GeoLLM/output/output_result/Task1/knn/one_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.3261, 召回率: 0.4369, F1: 0.3735
BERT Score: 
- Precision: 0.7701
- Recall: 0.9208
- F1: 0.8066

F:/GeoLLM/output/output_result/Task1/knn/two_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.3396, 召回率: 0.4494, F1: 0.3869
BERT Score: 
- Precision: 0.7849
- Recall: 0.9351
- F1: 0.8264

F:/GeoLLM/output/output_result/Task1/knn/three_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.3861, 召回率: 0.4869, F1: 0.4307
BERT Score: 
- Precision: 0.8048
- Recall: 0.9370
- F1: 0.8417

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/gemini-1p5-pro-002.json: 
Triple Match: 
精确率: 0.1421, 召回率: 0.2352, F1: 0.1772
BERT Score: 
- Precision: 0.5490
- Recall: 0.8373
- F1: 0.5754

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1769, 召回率: 0.2148, F1: 0.1941
BERT Score: 
- Precision: 0.6846
- Recall: 0.8621
- F1: 0.7209

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.3382, 召回率: 0.3844, F1: 0.3598
BERT Score: 
- Precision: 0.8116
- Recall: 0.9018
- F1: 0.8262

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1967, 召回率: 0.2438, F1: 0.2177
BERT Score: 
- Precision: 0.6939
- Recall: 0.8479
- F1: 0.7021

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.2238, 召回率: 0.2641, F1: 0.2423
BERT Score: 
- Precision: 0.7278
- Recall: 0.8190
- F1: 0.6915

F:/GeoLLM/output/output_result/Task1/knn/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.3339, 召回率: 0.3745, F1: 0.3531
BERT Score: 
- Precision: 0.8254
- Recall: 0.8996
- F1: 0.8338

F:/GeoLLM/output/output_result/Task1/knn/two_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.3699, 召回率: 0.4166, F1: 0.3918
BERT Score: 
- Precision: 0.8276
- Recall: 0.9025
- F1: 0.8294

F:/GeoLLM/output/output_result/Task1/knn/three_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.4141, 召回率: 0.4501, F1: 0.4314
BERT Score: 
- Precision: 0.8479
- Recall: 0.8966
- F1: 0.8341

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1486, 召回率: 0.1958, F1: 0.1690
BERT Score: 
- Precision: 0.6336
- Recall: 0.8582
- F1: 0.6836

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2412, 召回率: 0.2792, F1: 0.2588
BERT Score: 
- Precision: 0.7486
- Recall: 0.8745
- F1: 0.7717

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2245, 召回率: 0.2569, F1: 0.2396
BERT Score: 
- Precision: 0.7556
- Recall: 0.8760
- F1: 0.7768

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2371, 召回率: 0.2707, F1: 0.2528
BERT Score: 
- Precision: 0.7720
- Recall: 0.8848
- F1: 0.7944

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2431, 召回率: 0.2852, F1: 0.2625
BERT Score: 
- Precision: 0.7612
- Recall: 0.8815
- F1: 0.7845

F:/GeoLLM/output/output_result/Task1/knn/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.3854, 召回率: 0.4244, F1: 0.4040
BERT Score: 
- Precision: 0.8434
- Recall: 0.9120
- F1: 0.8554

F:/GeoLLM/output/output_result/Task1/knn/two_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.4002, 召回率: 0.4376, F1: 0.4181
BERT Score: 
- Precision: 0.8593
- Recall: 0.9167
- F1: 0.8671

F:/GeoLLM/output/output_result/Task1/knn/three_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.4372, 召回率: 0.4823, F1: 0.4586
BERT Score: 
- Precision: 0.8617
- Recall: 0.9193
- F1: 0.8669

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2007, 召回率: 0.2332, F1: 0.2157
BERT Score: 
- Precision: 0.7208
- Recall: 0.8353
- F1: 0.7136

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.1789, 召回率: 0.2556, F1: 0.2104
BERT Score: 
- Precision: 0.6563
- Recall: 0.8950
- F1: 0.7201

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.1950, 召回率: 0.2628, F1: 0.2239
BERT Score: 
- Precision: 0.6971
- Recall: 0.8963
- F1: 0.7505

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.2103, 召回率: 0.2681, F1: 0.2357
BERT Score: 
- Precision: 0.7241
- Recall: 0.8879
- F1: 0.7629

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.2206, 召回率: 0.2786, F1: 0.2462
BERT Score: 
- Precision: 0.7310
- Recall: 0.8962
- F1: 0.7709

F:/GeoLLM/output/output_result/Task1/knn/one_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.3576, 召回率: 0.4133, F1: 0.3834
BERT Score: 
- Precision: 0.8340
- Recall: 0.9185
- F1: 0.8534

F:/GeoLLM/output/output_result/Task1/knn/two_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.3911, 召回率: 0.4422, F1: 0.4150
BERT Score: 
- Precision: 0.8438
- Recall: 0.9203
- F1: 0.8591

F:/GeoLLM/output/output_result/Task1/knn/three_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.3889, 召回率: 0.4356, F1: 0.4109
BERT Score: 
- Precision: 0.8524
- Recall: 0.9154
- F1: 0.8602

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.1636, 召回率: 0.2411, F1: 0.1950
BERT Score: 
- Precision: 0.6327
- Recall: 0.8946
- F1: 0.6984

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1658, 召回率: 0.2196, F1: 0.1889
BERT Score: 
- Precision: 0.6343
- Recall: 0.8751
- F1: 0.6903

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1680, 召回率: 0.2181, F1: 0.1898
BERT Score: 
- Precision: 0.6558
- Recall: 0.8717
- F1: 0.7030

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.2117, 召回率: 0.2602, F1: 0.2334
BERT Score: 
- Precision: 0.7043
- Recall: 0.8718
- F1: 0.7373

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.2331, 召回率: 0.2884, F1: 0.2579
BERT Score: 
- Precision: 0.7111
- Recall: 0.8849
- F1: 0.7502

F:/GeoLLM/output/output_result/Task1/knn/one_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.3340, 召回率: 0.4126, F1: 0.3692
BERT Score: 
- Precision: 0.7722
- Recall: 0.9186
- F1: 0.8084

F:/GeoLLM/output/output_result/Task1/knn/two_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.3668, 召回率: 0.4297, F1: 0.3958
BERT Score: 
- Precision: 0.8028
- Recall: 0.9187
- F1: 0.8300

F:/GeoLLM/output/output_result/Task1/knn/three_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.4063, 召回率: 0.4671, F1: 0.4346
BERT Score: 
- Precision: 0.8284
- Recall: 0.9252
- F1: 0.8523

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/meta-llama/Meta-Llama-3p1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1392, 召回率: 0.1945, F1: 0.1623
BERT Score: 
- Precision: 0.6009
- Recall: 0.8681
- F1: 0.6615

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1509, 召回率: 0.1886, F1: 0.1676
BERT Score: 
- Precision: 0.6737
- Recall: 0.8676
- F1: 0.7118

F:/GeoLLM/output/output_result/Task1/nomal/one_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1823, 召回率: 0.2194, F1: 0.1992
BERT Score: 
- Precision: 0.7200
- Recall: 0.8758
- F1: 0.7508

F:/GeoLLM/output/output_result/Task1/nomal/two_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.2145, 召回率: 0.2510, F1: 0.2313
BERT Score: 
- Precision: 0.7431
- Recall: 0.8781
- F1: 0.7696

F:/GeoLLM/output/output_result/Task1/nomal/three_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1974, 召回率: 0.2221, F1: 0.2090
BERT Score: 
- Precision: 0.7576
- Recall: 0.8612
- F1: 0.7652

F:/GeoLLM/output/output_result/Task1/knn/one_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.3213, 召回率: 0.3699, F1: 0.3439
BERT Score: 
- Precision: 0.8121
- Recall: 0.8985
- F1: 0.8252

F:/GeoLLM/output/output_result/Task1/knn/two_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.3339, 召回率: 0.3791, F1: 0.3551
BERT Score: 
- Precision: 0.8259
- Recall: 0.9109
- F1: 0.8412

F:/GeoLLM/output/output_result/Task1/knn/three_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.3434, 召回率: 0.3962, F1: 0.3679
BERT Score: 
- Precision: 0.8269
- Recall: 0.9120
- F1: 0.8418

F:/GeoLLM/output/output_result/Task1/Knowledge-guided/one_shot/Qwen/Qwen2p5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1376, 召回率: 0.1754, F1: 0.1542
BERT Score: 
- Precision: 0.6612
- Recall: 0.8565
- F1: 0.6937

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0854, 召回率: 0.1064, F1: 0.0947
BERT Score: 
- Precision: 0.6277
- Recall: 0.8255
- F1: 0.6628

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1865, 召回率: 0.2050, F1: 0.1953
BERT Score: 
- Precision: 0.7593
- Recall: 0.8565
- F1: 0.7683

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0854, 召回率: 0.1064, F1: 0.0947
BERT Score: 
- Precision: 0.6277
- Recall: 0.8255
- F1: 0.6628

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1865, 召回率: 0.2050, F1: 0.1953
BERT Score: 
- Precision: 0.7593
- Recall: 0.8565
- F1: 0.7683

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0854, 召回率: 0.1064, F1: 0.0947
BERT Score: 
- Precision: 0.6277
- Recall: 0.8255
- F1: 0.6628

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1865, 召回率: 0.2050, F1: 0.1953
BERT Score: 
- Precision: 0.7593
- Recall: 0.8565
- F1: 0.7683

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.1816, 召回率: 0.2332, F1: 0.2042
BERT Score: 
- Precision: 0.6556
- Recall: 0.8752
- F1: 0.7035

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0854, 召回率: 0.1064, F1: 0.0947
BERT Score: 
- Precision: 0.6277
- Recall: 0.8255
- F1: 0.6628

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1865, 召回率: 0.2050, F1: 0.1953
BERT Score: 
- Precision: 0.7593
- Recall: 0.8565
- F1: 0.7683

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0854, 召回率: 0.1064, F1: 0.0947
BERT Score: 
- Precision: 0.6277
- Recall: 0.8255
- F1: 0.6628

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1865, 召回率: 0.2050, F1: 0.1953
BERT Score: 
- Precision: 0.7593
- Recall: 0.8565
- F1: 0.7683

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1457, 召回率: 0.2365, F1: 0.1804
BERT Score: 
- Precision: 0.5487
- Recall: 0.8703
- F1: 0.6166

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.1816, 召回率: 0.2332, F1: 0.2042
BERT Score: 
- Precision: 0.6556
- Recall: 0.8752
- F1: 0.7035

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0897, 召回率: 0.1189, F1: 0.1023
BERT Score: 
- Precision: 0.6092
- Recall: 0.8380
- F1: 0.6564

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.1950, 召回率: 0.2530, F1: 0.2203
BERT Score: 
- Precision: 0.6631
- Recall: 0.8817
- F1: 0.7147

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0803, 召回率: 0.1104, F1: 0.0930
BERT Score: 
- Precision: 0.6054
- Recall: 0.8461
- F1: 0.6564

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0972, 召回率: 0.1261, F1: 0.1098
BERT Score: 
- Precision: 0.5982
- Recall: 0.8324
- F1: 0.6441

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0883, 召回率: 0.1078, F1: 0.0971
BERT Score: 
- Precision: 0.6424
- Recall: 0.8363
- F1: 0.6804

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0911, 召回率: 0.1124, F1: 0.1006
BERT Score: 
- Precision: 0.6166
- Recall: 0.8276
- F1: 0.6575

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.1869, 召回率: 0.2385, F1: 0.2096
BERT Score: 
- Precision: 0.6602
- Recall: 0.8822
- F1: 0.7137

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0774, 召回率: 0.0867, F1: 0.0818
BERT Score: 
- Precision: 0.6669
- Recall: 0.8151
- F1: 0.6866

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0774, 召回率: 0.0867, F1: 0.0818
BERT Score: 
- Precision: 0.6669
- Recall: 0.8151
- F1: 0.6866

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo_0407.json: 
Triple Match: 
精确率: 0.0911, 召回率: 0.1124, F1: 0.1006
BERT Score: 
- Precision: 0.6166
- Recall: 0.8276
- F1: 0.6575

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2110, 召回率: 0.2622, F1: 0.2338
BERT Score: 
- Precision: 0.6775
- Recall: 0.8750
- F1: 0.7180

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1008, 召回率: 0.1321, F1: 0.1143
BERT Score: 
- Precision: 0.6100
- Recall: 0.8424
- F1: 0.6610

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo_0407.json: 
Triple Match: 
精确率: 0.0911, 召回率: 0.1124, F1: 0.1006
BERT Score: 
- Precision: 0.6166
- Recall: 0.8276
- F1: 0.6575

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo_old.json: 
Triple Match: 
精确率: 0.0854, 召回率: 0.1064, F1: 0.0947
BERT Score: 
- Precision: 0.6277
- Recall: 0.8255
- F1: 0.6628

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0661, 召回率: 0.0834, F1: 0.0738
BERT Score: 
- Precision: 0.6572
- Recall: 0.8299
- F1: 0.6880

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2412, 召回率: 0.2792, F1: 0.2588
BERT Score: 
- Precision: 0.7486
- Recall: 0.8745
- F1: 0.7717

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1008, 召回率: 0.1321, F1: 0.1143
BERT Score: 
- Precision: 0.6100
- Recall: 0.8424
- F1: 0.6610

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2110, 召回率: 0.2622, F1: 0.2338
BERT Score: 
- Precision: 0.6775
- Recall: 0.8750
- F1: 0.7180

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0661, 召回率: 0.0834, F1: 0.0738
BERT Score: 
- Precision: 0.6572
- Recall: 0.8299
- F1: 0.6880

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/old/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2167, 召回率: 0.2477, F1: 0.2311
BERT Score: 
- Precision: 0.7468
- Recall: 0.8548
- F1: 0.7492

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1008, 召回率: 0.1321, F1: 0.1143
BERT Score: 
- Precision: 0.6100
- Recall: 0.8424
- F1: 0.6610

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2110, 召回率: 0.2622, F1: 0.2338
BERT Score: 
- Precision: 0.6775
- Recall: 0.8750
- F1: 0.7180

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1886, 召回率: 0.2208, F1: 0.2034
BERT Score: 
- Precision: 0.7485
- Recall: 0.8543
- F1: 0.7526

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2477, 召回率: 0.2523, F1: 0.2500
BERT Score: 
- Precision: 0.8040
- Recall: 0.8391
- F1: 0.7838

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/old/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0392, 召回率: 0.0480, F1: 0.0432
BERT Score: 
- Precision: 0.6440
- Recall: 0.8230
- F1: 0.6795

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/old/gpt-4o.json: 
Triple Match: 
精确率: 0.1708, 召回率: 0.2004, F1: 0.1844
BERT Score: 
- Precision: 0.7403
- Recall: 0.8469
- F1: 0.7416

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/old/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2167, 召回率: 0.2477, F1: 0.2311
BERT Score: 
- Precision: 0.7468
- Recall: 0.8548
- F1: 0.7492

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1008, 召回率: 0.1321, F1: 0.1143
BERT Score: 
- Precision: 0.6100
- Recall: 0.8424
- F1: 0.6610

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2477, 召回率: 0.2523, F1: 0.2500
BERT Score: 
- Precision: 0.8040
- Recall: 0.8391
- F1: 0.7838

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2110, 召回率: 0.2622, F1: 0.2338
BERT Score: 
- Precision: 0.6775
- Recall: 0.8750
- F1: 0.7180

F:/GeoLLM/output/output_result/Task1/nomal/zero_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2412, 召回率: 0.2792, F1: 0.2588
BERT Score: 
- Precision: 0.7486
- Recall: 0.8745
- F1: 0.7717

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1008, 召回率: 0.1321, F1: 0.1143
BERT Score: 
- Precision: 0.6100
- Recall: 0.8424
- F1: 0.6610

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2477, 召回率: 0.2523, F1: 0.2500
BERT Score: 
- Precision: 0.8040
- Recall: 0.8391
- F1: 0.7838

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2110, 召回率: 0.2622, F1: 0.2338
BERT Score: 
- Precision: 0.6775
- Recall: 0.8750
- F1: 0.7180

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0915, 召回率: 0.1183, F1: 0.1032
BERT Score: 
- Precision: 0.6219
- Recall: 0.8321
- F1: 0.6612

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2088, 召回率: 0.2313, F1: 0.2195
BERT Score: 
- Precision: 0.7561
- Recall: 0.8614
- F1: 0.7674

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0915, 召回率: 0.1183, F1: 0.1032
BERT Score: 
- Precision: 0.6219
- Recall: 0.8321
- F1: 0.6612

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2088, 召回率: 0.2313, F1: 0.2195
BERT Score: 
- Precision: 0.7561
- Recall: 0.8614
- F1: 0.7674

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1764, 召回率: 0.1958, F1: 0.1856
BERT Score: 
- Precision: 0.7228
- Recall: 0.8386
- F1: 0.7236

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0915, 召回率: 0.1183, F1: 0.1032
BERT Score: 
- Precision: 0.6219
- Recall: 0.8321
- F1: 0.6612

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2088, 召回率: 0.2313, F1: 0.2195
BERT Score: 
- Precision: 0.7561
- Recall: 0.8614
- F1: 0.7674

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1795, 召回率: 0.2576, F1: 0.2115
BERT Score: 
- Precision: 0.5958
- Recall: 0.8605
- F1: 0.6324

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1764, 召回率: 0.1958, F1: 0.1856
BERT Score: 
- Precision: 0.7228
- Recall: 0.8386
- F1: 0.7236

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1947, 召回率: 0.2135, F1: 0.2037
BERT Score: 
- Precision: 0.7252
- Recall: 0.8467
- F1: 0.7364

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1880, 召回率: 0.2464, F1: 0.2132
BERT Score: 
- Precision: 0.6610
- Recall: 0.8657
- F1: 0.6977

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2156, 召回率: 0.2582, F1: 0.2350
BERT Score: 
- Precision: 0.7143
- Recall: 0.8759
- F1: 0.7443

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1880, 召回率: 0.2464, F1: 0.2132
BERT Score: 
- Precision: 0.6610
- Recall: 0.8657
- F1: 0.6977

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2508, 召回率: 0.2733, F1: 0.2616
BERT Score: 
- Precision: 0.7737
- Recall: 0.8686
- F1: 0.7863

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2078, 召回率: 0.2267, F1: 0.2168
BERT Score: 
- Precision: 0.7335
- Recall: 0.8506
- F1: 0.7447

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2531, 召回率: 0.2392, F1: 0.2459
BERT Score: 
- Precision: 0.8413
- Recall: 0.8209
- F1: 0.7944

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2078, 召回率: 0.2267, F1: 0.2168
BERT Score: 
- Precision: 0.7335
- Recall: 0.8506
- F1: 0.7447

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1579, 召回率: 0.1616, F1: 0.1597
BERT Score: 
- Precision: 0.7075
- Recall: 0.7944
- F1: 0.6799

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2531, 召回率: 0.2392, F1: 0.2459
BERT Score: 
- Precision: 0.8413
- Recall: 0.8209
- F1: 0.7944

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1952, 召回率: 0.2037, F1: 0.1994
BERT Score: 
- Precision: 0.7331
- Recall: 0.8076
- F1: 0.6983

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1913, 召回率: 0.2017, F1: 0.1964
BERT Score: 
- Precision: 0.7438
- Recall: 0.8325
- F1: 0.7387

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2078, 召回率: 0.2267, F1: 0.2168
BERT Score: 
- Precision: 0.7335
- Recall: 0.8506
- F1: 0.7447

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1652, 召回率: 0.1649, F1: 0.1651
BERT Score: 
- Precision: 0.7611
- Recall: 0.8210
- F1: 0.7411

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1855, 召回率: 0.1971, F1: 0.1911
BERT Score: 
- Precision: 0.7315
- Recall: 0.8317
- F1: 0.7301

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3_0420.json: 
Triple Match: 
精确率: 0.2110, 召回率: 0.2622, F1: 0.2338
BERT Score: 
- Precision: 0.6775
- Recall: 0.8750
- F1: 0.7180

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3_0421.json: 
Triple Match: 
精确率: 0.2156, 召回率: 0.2582, F1: 0.2350
BERT Score: 
- Precision: 0.7143
- Recall: 0.8759
- F1: 0.7443

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o_knowledge.json: 
Triple Match: 
精确率: 0.2088, 召回率: 0.2313, F1: 0.2195
BERT Score: 
- Precision: 0.7561
- Recall: 0.8614
- F1: 0.7674

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0963, 召回率: 0.1242, F1: 0.1085
BERT Score: 
- Precision: 0.6370
- Recall: 0.8426
- F1: 0.6786

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0963, 召回率: 0.1242, F1: 0.1085
BERT Score: 
- Precision: 0.6370
- Recall: 0.8426
- F1: 0.6786

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/gpt-4o.json: 
Triple Match: 
精确率: 0.2133, 召回率: 0.2451, F1: 0.2281
BERT Score: 
- Precision: 0.7142
- Recall: 0.8510
- F1: 0.7299

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1548, 召回率: 0.2280, F1: 0.1844
BERT Score: 
- Precision: 0.5858
- Recall: 0.8309
- F1: 0.6021

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1725, 召回率: 0.1965, F1: 0.1837
BERT Score: 
- Precision: 0.6876
- Recall: 0.8331
- F1: 0.7072

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2314, 召回率: 0.2661, F1: 0.2476
BERT Score: 
- Precision: 0.7174
- Recall: 0.8141
- F1: 0.6847

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1477, 召回率: 0.2096, F1: 0.1733
BERT Score: 
- Precision: 0.5923
- Recall: 0.8700
- F1: 0.6548

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1566, 召回率: 0.1846, F1: 0.1695
BERT Score: 
- Precision: 0.6896
- Recall: 0.8407
- F1: 0.7020

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/gpt-3.5-turbo_one_shot.json: 
Triple Match: 
精确率: 0.1059, 召回率: 0.1117, F1: 0.1087
BERT Score: 
- Precision: 0.6996
- Recall: 0.7882
- F1: 0.6752

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/gpt-4o_one_shot.json: 
Triple Match: 
精确率: 0.2548, 召回率: 0.2503, F1: 0.2526
BERT Score: 
- Precision: 0.8144
- Recall: 0.8364
- F1: 0.7853

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/gemini-1.5-pro-002_one_shot.json: 
Triple Match: 
精确率: 0.1899, 召回率: 0.2549, F1: 0.2177
BERT Score: 
- Precision: 0.6432
- Recall: 0.8401
- F1: 0.6515

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/claude-3-5-haiku-20241022_one_shot.json: 
Triple Match: 
精确率: 0.1953, 召回率: 0.2181, F1: 0.2061
BERT Score: 
- Precision: 0.6993
- Recall: 0.8323
- F1: 0.7127

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/deepseek-ai/DeepSeek-V3_one_shot.json: 
Triple Match: 
精确率: 0.2845, 召回率: 0.2996, F1: 0.2918
BERT Score: 
- Precision: 0.7700
- Recall: 0.8256
- F1: 0.7364

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/meta-llama/Meta-Llama-3.1-405B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.2087, 召回率: 0.2293, F1: 0.2185
BERT Score: 
- Precision: 0.7350
- Recall: 0.8421
- F1: 0.7374

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/Qwen/Qwen2.5-72B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.1929, 召回率: 0.2011, F1: 0.1969
BERT Score: 
- Precision: 0.7623
- Recall: 0.8327
- F1: 0.7481

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_choice/deepseek-ai/DeepSeek-V3_one_shot.json: 
Triple Match: 
精确率: 0.2808, 召回率: 0.3009, F1: 0.2905
BERT Score: 
- Precision: 0.7793
- Recall: 0.8269
- F1: 0.7408

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_choice/deepseek-ai/DeepSeek-V3_guide.json: 
Triple Match: 
精确率: 0.2191, 召回率: 0.2562, F1: 0.2362
BERT Score: 
- Precision: 0.7138
- Recall: 0.8409
- F1: 0.7103

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.1939, 召回率: 0.2845, F1: 0.2306
BERT Score: 
- Precision: 0.6166
- Recall: 0.8953
- F1: 0.6824

F:/GeoLLM/output/Knowledge-guided_rerun/nomal/deepseek-ai/DeepSeek-R1_one_shot.json: 
Triple Match: 
精确率: 0.2547, 召回率: 0.3233, F1: 0.2849
BERT Score: 
- Precision: 0.7048
- Recall: 0.8891
- F1: 0.7405

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-3.5-turbo_one_shot.json: 
Triple Match: 
精确率: 0.1081, 召回率: 0.1117, F1: 0.1099
BERT Score: 
- Precision: 0.7172
- Recall: 0.7529
- F1: 0.6528

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-4o_one_shot.json: 
Triple Match: 
精确率: 0.2971, 召回率: 0.2444, F1: 0.2682
BERT Score: 
- Precision: 0.8766
- Recall: 0.7751
- F1: 0.7691

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gemini-1.5-pro-002_one_shot.json: 
Triple Match: 
精确率: 0.2953, 召回率: 0.3489, F1: 0.3199
BERT Score: 
- Precision: 0.7310
- Recall: 0.8277
- F1: 0.6931

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/claude-3-5-haiku-20241022_one_shot.json: 
Triple Match: 
精确率: 0.2339, 召回率: 0.2436, F1: 0.2387
BERT Score: 
- Precision: 0.7454
- Recall: 0.8332
- F1: 0.7411

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/deepseek-ai/DeepSeek-V3_one_shot.json: 
Triple Match: 
精确率: 0.2908, 召回率: 0.2963, F1: 0.2935
BERT Score: 
- Precision: 0.8031
- Recall: 0.8425
- F1: 0.7768

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/meta-llama/Meta-Llama-3.1-405B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.2341, 召回率: 0.2470, F1: 0.2404
BERT Score: 
- Precision: 0.7700
- Recall: 0.8487
- F1: 0.7676

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/Qwen/Qwen2.5-72B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.2176, 召回率: 0.2240, F1: 0.2208
BERT Score: 
- Precision: 0.7709
- Recall: 0.8353
- F1: 0.7581

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-3.5-turbo_one_shot.json: 
Triple Match: 
精确率: 0.1081, 召回率: 0.1117, F1: 0.1099
BERT Score: 
- Precision: 0.7172
- Recall: 0.7529
- F1: 0.6528

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-4o_one_shot.json: 
Triple Match: 
精确率: 0.2971, 召回率: 0.2444, F1: 0.2682
BERT Score: 
- Precision: 0.8766
- Recall: 0.7751
- F1: 0.7691

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gemini-1.5-pro-002_one_shot.json: 
Triple Match: 
精确率: 0.2953, 召回率: 0.3489, F1: 0.3199
BERT Score: 
- Precision: 0.7310
- Recall: 0.8277
- F1: 0.6931

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/claude-3-5-haiku-20241022_one_shot.json: 
Triple Match: 
精确率: 0.2339, 召回率: 0.2436, F1: 0.2387
BERT Score: 
- Precision: 0.7454
- Recall: 0.8332
- F1: 0.7411

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/deepseek-ai/DeepSeek-V3_one_shot.json: 
Triple Match: 
精确率: 0.2908, 召回率: 0.2963, F1: 0.2935
BERT Score: 
- Precision: 0.8031
- Recall: 0.8425
- F1: 0.7768

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/meta-llama/Meta-Llama-3.1-405B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.2341, 召回率: 0.2470, F1: 0.2404
BERT Score: 
- Precision: 0.7700
- Recall: 0.8487
- F1: 0.7676

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/Qwen/Qwen2.5-72B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.2176, 召回率: 0.2240, F1: 0.2208
BERT Score: 
- Precision: 0.7709
- Recall: 0.8353
- F1: 0.7581

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1016, 召回率: 0.1294, F1: 0.1138
BERT Score: 
- Precision: 0.6323
- Recall: 0.8392
- F1: 0.6721

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-4o.json: 
Triple Match: 
精确率: 0.2253, 召回率: 0.2365, F1: 0.2308
BERT Score: 
- Precision: 0.7883
- Recall: 0.8503
- F1: 0.7810

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1626, 召回率: 0.2267, F1: 0.1894
BERT Score: 
- Precision: 0.6117
- Recall: 0.7841
- F1: 0.5770

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1853, 召回率: 0.2214, F1: 0.2017
BERT Score: 
- Precision: 0.6501
- Recall: 0.8473
- F1: 0.6889

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2339, 召回率: 0.2760, F1: 0.2532
BERT Score: 
- Precision: 0.7120
- Recall: 0.8565
- F1: 0.7217

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-3.5-turbo_one_shot.json: 
Triple Match: 
精确率: 0.1081, 召回率: 0.1117, F1: 0.1099
BERT Score: 
- Precision: 0.7172
- Recall: 0.7529
- F1: 0.6528

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-4o_one_shot.json: 
Triple Match: 
精确率: 0.2971, 召回率: 0.2444, F1: 0.2682
BERT Score: 
- Precision: 0.8766
- Recall: 0.7751
- F1: 0.7691

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gemini-1.5-pro-002_one_shot.json: 
Triple Match: 
精确率: 0.2953, 召回率: 0.3489, F1: 0.3199
BERT Score: 
- Precision: 0.7310
- Recall: 0.8277
- F1: 0.6931

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/claude-3-5-haiku-20241022_one_shot.json: 
Triple Match: 
精确率: 0.2339, 召回率: 0.2436, F1: 0.2387
BERT Score: 
- Precision: 0.7454
- Recall: 0.8332
- F1: 0.7411

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/deepseek-ai/DeepSeek-V3_one_shot.json: 
Triple Match: 
精确率: 0.2908, 召回率: 0.2963, F1: 0.2935
BERT Score: 
- Precision: 0.8031
- Recall: 0.8425
- F1: 0.7768

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/meta-llama/Meta-Llama-3.1-405B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.2341, 召回率: 0.2470, F1: 0.2404
BERT Score: 
- Precision: 0.7700
- Recall: 0.8487
- F1: 0.7676

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/Qwen/Qwen2.5-72B-Instruct_one_shot.json: 
Triple Match: 
精确率: 0.2176, 召回率: 0.2240, F1: 0.2208
BERT Score: 
- Precision: 0.7709
- Recall: 0.8353
- F1: 0.7581

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1016, 召回率: 0.1294, F1: 0.1138
BERT Score: 
- Precision: 0.6323
- Recall: 0.8392
- F1: 0.6721

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gpt-4o.json: 
Triple Match: 
精确率: 0.2253, 召回率: 0.2365, F1: 0.2308
BERT Score: 
- Precision: 0.7883
- Recall: 0.8503
- F1: 0.7810

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1626, 召回率: 0.2267, F1: 0.1894
BERT Score: 
- Precision: 0.6117
- Recall: 0.7841
- F1: 0.5770

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1853, 召回率: 0.2214, F1: 0.2017
BERT Score: 
- Precision: 0.6501
- Recall: 0.8473
- F1: 0.6889

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2339, 召回率: 0.2760, F1: 0.2532
BERT Score: 
- Precision: 0.7120
- Recall: 0.8565
- F1: 0.7217

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1620, 召回率: 0.2234, F1: 0.1878
BERT Score: 
- Precision: 0.6236
- Recall: 0.8733
- F1: 0.6780

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1710, 召回率: 0.2181, F1: 0.1917
BERT Score: 
- Precision: 0.6653
- Recall: 0.8692
- F1: 0.7061

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/gpt-4o_konwledge_tri.json: 
Triple Match: 
精确率: 0.2531, 召回率: 0.2392, F1: 0.2459
BERT Score: 
- Precision: 0.8413
- Recall: 0.8209
- F1: 0.7944

F:/GeoLLM/output/Knowledge-guided_rerun/one_shot/deepseek-ai/DeepSeek-V3_konwledge_tri.json: 
Triple Match: 
精确率: 0.2078, 召回率: 0.2267, F1: 0.2168
BERT Score: 
- Precision: 0.7335
- Recall: 0.8506
- F1: 0.7447

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_only_tri/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2005, 召回率: 0.2208, F1: 0.2101
BERT Score: 
- Precision: 0.7373
- Recall: 0.8532
- F1: 0.7495

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/deepseek-ai/DeepSeek-R1_guide.json: 
Triple Match: 
精确率: 0.2327, 召回率: 0.3397, F1: 0.2762
BERT Score: 
- Precision: 0.6238
- Recall: 0.9047
- F1: 0.6921

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_all/deepseek-ai/DeepSeek-R1_one_shot.json: 
Triple Match: 
精确率: 0.2829, 召回率: 0.3331, F1: 0.3060
BERT Score: 
- Precision: 0.7552
- Recall: 0.8813
- F1: 0.7735

F:/GeoLLM/output/Knowledge-guided_rerun/nomal_only_tri/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.2048, 召回率: 0.2523, F1: 0.2261
BERT Score: 
- Precision: 0.7166
- Recall: 0.8771
- F1: 0.7502

./output/Task1/nomal/zero_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0392, 召回率: 0.0480, F1: 0.0432
BERT Score: 
- Precision: 0.6440
- Recall: 0.8230
- F1: 0.6795

./output/Task1/nomal/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0854, 召回率: 0.0979, F1: 0.0912
BERT Score: 
- Precision: 0.6791
- Recall: 0.8185
- F1: 0.6938

./output/Task1/nomal/two_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1015, 召回率: 0.1216, F1: 0.1106
BERT Score: 
- Precision: 0.6860
- Recall: 0.8345
- F1: 0.7066

./output/Task1/nomal/three_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.1061, 召回率: 0.1275, F1: 0.1158
BERT Score: 
- Precision: 0.6904
- Recall: 0.8327
- F1: 0.7088

./output/Task1/knn/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.2115, 召回率: 0.2438, F1: 0.2265
BERT Score: 
- Precision: 0.7573
- Recall: 0.8712
- F1: 0.7803

./output/Task1/knn/two_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.2182, 召回率: 0.2589, F1: 0.2368
BERT Score: 
- Precision: 0.7407
- Recall: 0.8763
- F1: 0.7699

./output/Task1/knn/three_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.2134, 召回率: 0.2576, F1: 0.2334
BERT Score: 
- Precision: 0.7443
- Recall: 0.8750
- F1: 0.7670

./output/Task1/Knowledge-guided/one_shot/gpt-3.5-turbo.json: 
Triple Match: 
精确率: 0.0697, 召回率: 0.0834, F1: 0.0759
BERT Score: 
- Precision: 0.6656
- Recall: 0.8230
- F1: 0.6876

./output/Task1/nomal/zero_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1708, 召回率: 0.2004, F1: 0.1844
BERT Score: 
- Precision: 0.7403
- Recall: 0.8469
- F1: 0.7416

./output/Task1/nomal/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2081, 召回率: 0.2424, F1: 0.2240
BERT Score: 
- Precision: 0.7613
- Recall: 0.8716
- F1: 0.7780

./output/Task1/nomal/two_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2358, 召回率: 0.2648, F1: 0.2495
BERT Score: 
- Precision: 0.7846
- Recall: 0.8672
- F1: 0.7906

./output/Task1/nomal/three_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.2683, 召回率: 0.3029, F1: 0.2846
BERT Score: 
- Precision: 0.7899
- Recall: 0.8687
- F1: 0.7944

./output/Task1/knn/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.3464, 召回率: 0.3765, F1: 0.3608
BERT Score: 
- Precision: 0.8483
- Recall: 0.9018
- F1: 0.8524

./output/Task1/knn/two_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.4056, 召回率: 0.4376, F1: 0.4210
BERT Score: 
- Precision: 0.8624
- Recall: 0.9076
- F1: 0.8639

./output/Task1/knn/three_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.4176, 召回率: 0.4514, F1: 0.4338
BERT Score: 
- Precision: 0.8741
- Recall: 0.9116
- F1: 0.8735

./output/Task1/Knowledge-guided/one_shot/gpt-4o.json: 
Triple Match: 
精确率: 0.1836, 召回率: 0.2050, F1: 0.1937
BERT Score: 
- Precision: 0.7454
- Recall: 0.8488
- F1: 0.7533

./output/Task1/nomal/zero_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1627, 召回率: 0.2582, F1: 0.1996
BERT Score: 
- Precision: 0.6037
- Recall: 0.8142
- F1: 0.5859

./output/Task1/nomal/one_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1822, 召回率: 0.2871, F1: 0.2229
BERT Score: 
- Precision: 0.6319
- Recall: 0.9011
- F1: 0.6990

./output/Task1/nomal/two_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.2028, 召回率: 0.3003, F1: 0.2421
BERT Score: 
- Precision: 0.6702
- Recall: 0.9001
- F1: 0.7253

./output/Task1/nomal/three_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.2302, 召回率: 0.3338, F1: 0.2725
BERT Score: 
- Precision: 0.6866
- Recall: 0.8960
- F1: 0.7329

./output/Task1/knn/one_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.3261, 召回率: 0.4369, F1: 0.3735
BERT Score: 
- Precision: 0.7701
- Recall: 0.9208
- F1: 0.8066

./output/Task1/knn/two_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.3396, 召回率: 0.4494, F1: 0.3869
BERT Score: 
- Precision: 0.7849
- Recall: 0.9351
- F1: 0.8264

./output/Task1/knn/three_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.3861, 召回率: 0.4869, F1: 0.4307
BERT Score: 
- Precision: 0.8048
- Recall: 0.9370
- F1: 0.8417

./output/Task1/Knowledge-guided/one_shot/gemini-1.5-pro-002.json: 
Triple Match: 
精确率: 0.1421, 召回率: 0.2352, F1: 0.1772
BERT Score: 
- Precision: 0.5490
- Recall: 0.8373
- F1: 0.5754

./output/Task1/nomal/zero_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1767, 召回率: 0.2122, F1: 0.1928
BERT Score: 
- Precision: 0.6856
- Recall: 0.8539
- F1: 0.7146

./output/Task1/nomal/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1857, 召回率: 0.2300, F1: 0.2055
BERT Score: 
- Precision: 0.6829
- Recall: 0.8734
- F1: 0.7284

./output/Task1/nomal/two_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1967, 召回率: 0.2438, F1: 0.2177
BERT Score: 
- Precision: 0.6939
- Recall: 0.8479
- F1: 0.7021

./output/Task1/nomal/three_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.2238, 召回率: 0.2641, F1: 0.2423
BERT Score: 
- Precision: 0.7278
- Recall: 0.8190
- F1: 0.6915

./output/Task1/knn/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.3339, 召回率: 0.3745, F1: 0.3531
BERT Score: 
- Precision: 0.8254
- Recall: 0.8996
- F1: 0.8338

./output/Task1/knn/two_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.3699, 召回率: 0.4166, F1: 0.3918
BERT Score: 
- Precision: 0.8276
- Recall: 0.9025
- F1: 0.8294

./output/Task1/knn/three_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.4141, 召回率: 0.4501, F1: 0.4314
BERT Score: 
- Precision: 0.8479
- Recall: 0.8966
- F1: 0.8341

./output/Task1/Knowledge-guided/one_shot/claude-3-5-haiku-20241022.json: 
Triple Match: 
精确率: 0.1486, 召回率: 0.1958, F1: 0.1690
BERT Score: 
- Precision: 0.6336
- Recall: 0.8582
- F1: 0.6836

./output/Task1/nomal/zero_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2167, 召回率: 0.2477, F1: 0.2311
BERT Score: 
- Precision: 0.7468
- Recall: 0.8548
- F1: 0.7492

./output/Task1/nomal/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2245, 召回率: 0.2569, F1: 0.2396
BERT Score: 
- Precision: 0.7556
- Recall: 0.8760
- F1: 0.7768

./output/Task1/nomal/two_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2371, 召回率: 0.2707, F1: 0.2528
BERT Score: 
- Precision: 0.7720
- Recall: 0.8848
- F1: 0.7944

./output/Task1/nomal/three_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2431, 召回率: 0.2852, F1: 0.2625
BERT Score: 
- Precision: 0.7612
- Recall: 0.8815
- F1: 0.7845

./output/Task1/knn/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.3854, 召回率: 0.4244, F1: 0.4040
BERT Score: 
- Precision: 0.8434
- Recall: 0.9120
- F1: 0.8554

./output/Task1/knn/two_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.4002, 召回率: 0.4376, F1: 0.4181
BERT Score: 
- Precision: 0.8593
- Recall: 0.9167
- F1: 0.8671

./output/Task1/knn/three_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.4372, 召回率: 0.4823, F1: 0.4586
BERT Score: 
- Precision: 0.8617
- Recall: 0.9193
- F1: 0.8669

./output/Task1/Knowledge-guided/one_shot/deepseek-ai/DeepSeek-V3.json: 
Triple Match: 
精确率: 0.2007, 召回率: 0.2332, F1: 0.2157
BERT Score: 
- Precision: 0.7208
- Recall: 0.8353
- F1: 0.7136

./output/Task1/nomal/zero_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.1735, 召回率: 0.2424, F1: 0.2022
BERT Score: 
- Precision: 0.6707
- Recall: 0.8899
- F1: 0.7258

./output/Task1/nomal/one_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.0000, 召回率: 0.0000, F1: 0.0000
BERT Score: 
- Precision: 0.4077
- Recall: 0.5243
- F1: 0.4518

./output/Task1/nomal/two_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.2103, 召回率: 0.2681, F1: 0.2357
BERT Score: 
- Precision: 0.7241
- Recall: 0.8879
- F1: 0.7629

./output/Task1/nomal/three_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.2206, 召回率: 0.2786, F1: 0.2462
BERT Score: 
- Precision: 0.7310
- Recall: 0.8962
- F1: 0.7709

./output/Task1/knn/one_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.3576, 召回率: 0.4133, F1: 0.3834
BERT Score: 
- Precision: 0.8340
- Recall: 0.9185
- F1: 0.8534

./output/Task1/knn/two_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.3911, 召回率: 0.4422, F1: 0.4150
BERT Score: 
- Precision: 0.8438
- Recall: 0.9203
- F1: 0.8591

./output/Task1/knn/three_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.3889, 召回率: 0.4356, F1: 0.4109
BERT Score: 
- Precision: 0.8524
- Recall: 0.9154
- F1: 0.8602

./output/Task1/Knowledge-guided/one_shot/deepseek-ai/DeepSeek-R1.json: 
Triple Match: 
精确率: 0.1636, 召回率: 0.2411, F1: 0.1950
BERT Score: 
- Precision: 0.6327
- Recall: 0.8946
- F1: 0.6984

./output/Task1/nomal/zero_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1446, 召回率: 0.1886, F1: 0.1637
BERT Score: 
- Precision: 0.6266
- Recall: 0.8676
- F1: 0.6813

./output/Task1/nomal/one_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1740, 召回率: 0.2221, F1: 0.1952
BERT Score: 
- Precision: 0.6658
- Recall: 0.8708
- F1: 0.7122

./output/Task1/nomal/two_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.2117, 召回率: 0.2602, F1: 0.2334
BERT Score: 
- Precision: 0.7043
- Recall: 0.8718
- F1: 0.7373

./output/Task1/nomal/three_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.2331, 召回率: 0.2884, F1: 0.2579
BERT Score: 
- Precision: 0.7111
- Recall: 0.8849
- F1: 0.7502

./output/Task1/knn/one_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.3340, 召回率: 0.4126, F1: 0.3692
BERT Score: 
- Precision: 0.7722
- Recall: 0.9186
- F1: 0.8084

./output/Task1/knn/two_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.3668, 召回率: 0.4297, F1: 0.3958
BERT Score: 
- Precision: 0.8028
- Recall: 0.9187
- F1: 0.8300

./output/Task1/knn/three_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.4063, 召回率: 0.4671, F1: 0.4346
BERT Score: 
- Precision: 0.8284
- Recall: 0.9252
- F1: 0.8523

./output/Task1/Knowledge-guided/one_shot/meta-llama/Meta-Llama-3.1-405B-Instruct.json: 
Triple Match: 
精确率: 0.1392, 召回率: 0.1945, F1: 0.1623
BERT Score: 
- Precision: 0.6009
- Recall: 0.8681
- F1: 0.6615

./output/Task1/nomal/zero_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1529, 召回率: 0.1881, F1: 0.1687
BERT Score: 
- Precision: 0.6776
- Recall: 0.8645
- F1: 0.7163

./output/Task1/nomal/one_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1823, 召回率: 0.2194, F1: 0.1992
BERT Score: 
- Precision: 0.7200
- Recall: 0.8758
- F1: 0.7508

./output/Task1/nomal/two_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.2145, 召回率: 0.2510, F1: 0.2313
BERT Score: 
- Precision: 0.7431
- Recall: 0.8781
- F1: 0.7696

./output/Task1/nomal/three_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1974, 召回率: 0.2221, F1: 0.2090
BERT Score: 
- Precision: 0.7576
- Recall: 0.8612
- F1: 0.7652

./output/Task1/knn/one_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.3213, 召回率: 0.3699, F1: 0.3439
BERT Score: 
- Precision: 0.8121
- Recall: 0.8985
- F1: 0.8252

./output/Task1/knn/two_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.3339, 召回率: 0.3791, F1: 0.3551
BERT Score: 
- Precision: 0.8259
- Recall: 0.9109
- F1: 0.8412

./output/Task1/knn/three_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.3434, 召回率: 0.3962, F1: 0.3679
BERT Score: 
- Precision: 0.8269
- Recall: 0.9120
- F1: 0.8418

./output/Task1/Knowledge-guided/one_shot/Qwen/Qwen2.5-72B-Instruct.json: 
Triple Match: 
精确率: 0.1376, 召回率: 0.1754, F1: 0.1542
BERT Score: 
- Precision: 0.6612
- Recall: 0.8565
- F1: 0.6937

