Unnamed: 0 stringlengths 11 22 | R-Syn-1 stringlengths 14 14 | R-Syn-Max stringlengths 14 14 | R-Sem stringlengths 14 14 | S-Syn-1 stringlengths 14 14 | S-Syn-Max stringlengths 14 14 | S-Sem-R stringlengths 14 14 | S-Sem-W-1 stringlengths 14 14 | S-Sem-W-max stringlengths 14 14 | total stringlengths 14 14 |
|---|---|---|---|---|---|---|---|---|---|
Qwen-3.5-397B | 0.941 (±0.215) | 0.994 (±0.015) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.940 (±0.211) | 0.940 (±0.211) | 0.977 (±0.133) |
Claude Opus 4.6 | 0.934 (±0.234) | 0.996 (±0.013) | 0.657 (±0.415) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.747 (±0.362) | 0.837 (±0.311) | 0.896 (±0.270) |
Claude Sonnet 4.6 | 0.934 (±0.234) | 0.996 (±0.013) | 0.282 (±0.300) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.747 (±0.362) | 0.797 (±0.338) | 0.844 (±0.321) |
Gemini 3 Flash Preview | 0.961 (±0.168) | 0.995 (±0.014) | 0.973 (±0.061) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.760 (±0.367) | 0.850 (±0.312) | 0.942 (±0.200) |
GPT5.2-chat | 0.962 (±0.168) | 0.995 (±0.014) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.807 (±0.332) | 0.877 (±0.276) | 0.955 (±0.178) |
GPT5.4 2026/03 | 0.934 (±0.234) | 0.996 (±0.013) | 0.998 (±0.020) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.647 (±0.388) | 0.687 (±0.381) | 0.908 (±0.253) |
Claude 3.5 Haiku | 0.937 (±0.203) | 0.984 (±0.029) | 0.779 (±0.395) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.817 (±0.325) | 0.887 (±0.266) | 0.925 (±0.232) |
Claude 3.5 Sonnet | 0.950 (±0.175) | 0.990 (±0.022) | 0.832 (±0.370) | 0.980 (±0.125) | 1.000 (±0.000) | 1.000 (±0.000) | 0.857 (±0.295) | 0.857 (±0.295) | 0.933 (±0.222) |
Deepseek-Coder-33B | 0.773 (±0.366) | 0.882 (±0.269) | 0.263 (±0.297) | 0.943 (±0.221) | 0.984 (±0.112) | 0.313 (±0.309) | 0.689 (±0.379) | 0.703 (±0.374) | 0.694 (±0.396) |
Deepseek-R1 | 0.955 (±0.174) | 0.991 (±0.020) | 0.992 (±0.089) | 0.935 (±0.247) | 1.000 (±0.000) | 1.000 (±0.000) | 0.746 (±0.382) | 0.832 (±0.316) | 0.931 (±0.226) |
Deepseek-Chat-v3 | 0.843 (±0.347) | 0.991 (±0.020) | 0.591 (±0.466) | 0.957 (±0.202) | 0.997 (±0.050) | 0.923 (±0.214) | 0.702 (±0.384) | 0.782 (±0.348) | 0.848 (±0.326) |
Gemini 1.5 Flash | 0.920 (±0.242) | 0.983 (±0.028) | 0.878 (±0.325) | 0.865 (±0.324) | 0.910 (±0.272) | 1.000 (±0.000) | 0.850 (±0.304) | 0.850 (±0.304) | 0.907 (±0.263) |
Gemini 1.5 Pro | 0.887 (±0.291) | 0.966 (±0.127) | 0.796 (±0.399) | 0.845 (±0.339) | 0.905 (±0.286) | 1.000 (±0.000) | 0.883 (±0.276) | 0.883 (±0.276) | 0.896 (±0.282) |
Gemini 2.0 Flash Exp | 0.986 (±0.025) | 0.988 (±0.024) | 0.931 (±0.197) | 0.994 (±0.079) | 1.000 (±0.000) | 1.000 (±0.000) | 0.604 (±0.394) | 0.657 (±0.387) | 0.895 (±0.260) |
Llama-3.1-70B | 0.908 (±0.234) | 0.973 (±0.034) | 0.559 (±0.484) | 0.997 (±0.050) | 0.997 (±0.050) | 1.000 (±0.000) | 0.694 (±0.381) | 0.754 (±0.361) | 0.860 (±0.311) |
Llama-3.1-8B | 0.779 (±0.375) | 0.915 (±0.228) | 0.462 (±0.421) | 0.401 (±0.475) | 0.521 (±0.477) | 0.535 (±0.377) | 0.273 (±0.401) | 0.355 (±0.425) | 0.530 (±0.452) |
Llama-3.2-1B | 0.250 (±0.366) | 0.411 (±0.409) | 0.159 (±0.254) | 0.026 (±0.143) | 0.079 (±0.260) | 0.021 (±0.070) | 0.010 (±0.050) | 0.027 (±0.073) | 0.123 (±0.276) |
Llama-3.2-3B | 0.402 (±0.452) | 0.773 (±0.332) | 0.344 (±0.397) | 0.196 (±0.374) | 0.322 (±0.444) | 0.308 (±0.373) | 0.120 (±0.256) | 0.212 (±0.308) | 0.335 (±0.416) |
Llama-3.3-70B | 0.975 (±0.032) | 0.978 (±0.029) | 0.595 (±0.487) | 0.985 (±0.122) | 1.000 (±0.000) | 1.000 (±0.000) | 0.617 (±0.398) | 0.671 (±0.385) | 0.853 (±0.318) |
Llama-3.0-70B | 0.961 (±0.114) | 0.974 (±0.033) | 0.523 (±0.480) | 0.955 (±0.208) | 0.990 (±0.099) | 1.000 (±0.000) | 0.645 (±0.405) | 0.731 (±0.367) | 0.847 (±0.324) |
Llama-3.0-8B | 0.586 (±0.426) | 0.632 (±0.416) | 0.219 (±0.290) | 0.271 (±0.445) | 0.425 (±0.488) | 0.615 (±0.337) | 0.281 (±0.397) | 0.445 (±0.417) | 0.434 (±0.435) |
Llama-4-Maverick | 0.870 (±0.241) | 0.974 (±0.033) | 0.655 (±0.465) | 0.960 (±0.196) | 1.000 (±0.000) | 0.910 (±0.244) | 0.687 (±0.381) | 0.815 (±0.327) | 0.859 (±0.305) |
GPT3.5 2024/01 | 0.975 (±0.126) | 0.995 (±0.014) | 0.411 (±0.442) | 0.944 (±0.230) | 1.000 (±0.000) | 0.696 (±0.374) | 0.674 (±0.387) | 0.707 (±0.376) | 0.800 (±0.356) |
GPT4o 2024/11 | 0.937 (±0.212) | 0.986 (±0.024) | 0.726 (±0.377) | 1.000 (±0.000) | 1.000 (±0.000) | 0.881 (±0.183) | 0.817 (±0.325) | 0.867 (±0.286) | 0.902 (±0.244) |
GPT4o-mini 2024/07 | 0.919 (±0.232) | 0.983 (±0.030) | 0.384 (±0.415) | 0.921 (±0.246) | 0.960 (±0.174) | 0.962 (±0.089) | 0.709 (±0.385) | 0.777 (±0.349) | 0.827 (±0.333) |
GPTo1-mini 2024/09 | 0.835 (±0.351) | 0.992 (±0.018) | 0.994 (±0.031) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.697 (±0.379) | 0.767 (±0.354) | 0.911 (±0.251) |
GPTo1-pre 2024/09 | 0.911 (±0.256) | 0.992 (±0.020) | 0.658 (±0.373) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.742 (±0.365) | 0.812 (±0.329) | 0.889 (±0.268) |
OpenCoder-8B | 0.746 (±0.405) | 0.817 (±0.354) | 0.167 (±0.285) | 0.622 (±0.482) | 0.737 (±0.437) | 0.400 (±0.422) | 0.459 (±0.422) | 0.509 (±0.417) | 0.557 (±0.454) |
Phi-3.5-mini | 0.608 (±0.412) | 0.639 (±0.390) | 0.176 (±0.297) | 0.637 (±0.466) | 0.683 (±0.450) | 0.450 (±0.381) | 0.309 (±0.367) | 0.350 (±0.371) | 0.481 (±0.432) |
Phi-3.5-MoE | 0.831 (±0.296) | 0.841 (±0.287) | 0.517 (±0.421) | 0.808 (±0.391) | 0.932 (±0.238) | 0.688 (±0.185) | 0.637 (±0.394) | 0.648 (±0.389) | 0.738 (±0.359) |
Phi-3.0-medium-128k | 0.838 (±0.318) | 0.886 (±0.257) | 0.248 (±0.364) | 0.547 (±0.475) | 0.603 (±0.466) | 0.625 (±0.316) | 0.360 (±0.412) | 0.385 (±0.417) | 0.561 (±0.439) |
Phi-3.0-mini-128k | 0.582 (±0.424) | 0.660 (±0.388) | 0.263 (±0.333) | 0.486 (±0.479) | 0.549 (±0.480) | 0.428 (±0.336) | 0.231 (±0.291) | 0.245 (±0.292) | 0.431 (±0.415) |
Phi-3.0-small-128k | 0.346 (±0.394) | 0.432 (±0.385) | 0.284 (±0.364) | 0.366 (±0.427) | 0.394 (±0.429) | 0.593 (±0.487) | 0.278 (±0.352) | 0.300 (±0.356) | 0.374 (±0.413) |
Qwen-2.0-0.5B | 0.068 (±0.159) | 0.076 (±0.171) | 0.085 (±0.205) | 0.005 (±0.071) | 0.012 (±0.111) | 0.040 (±0.136) | 0.006 (±0.072) | 0.010 (±0.080) | 0.038 (±0.138) |
Qwen-2.0-1.5B | 0.126 (±0.294) | 0.145 (±0.314) | 0.222 (±0.349) | 0.293 (±0.448) | 0.351 (±0.465) | 0.154 (±0.196) | 0.105 (±0.177) | 0.115 (±0.182) | 0.189 (±0.332) |
Qwen-2.5-0.5B | 0.053 (±0.153) | 0.101 (±0.235) | 0.083 (±0.199) | 0.157 (±0.360) | 0.185 (±0.384) | 0.071 (±0.179) | 0.061 (±0.128) | 0.064 (±0.129) | 0.097 (±0.244) |
Qwen-2.5-14B | 0.781 (±0.393) | 0.922 (±0.245) | 0.331 (±0.432) | 0.897 (±0.303) | 0.910 (±0.286) | 0.933 (±0.240) | 0.658 (±0.378) | 0.671 (±0.374) | 0.763 (±0.390) |
Qwen-2.5-1.5B | 0.470 (±0.459) | 0.584 (±0.452) | 0.266 (±0.339) | 0.494 (±0.485) | 0.527 (±0.482) | 0.127 (±0.268) | 0.186 (±0.272) | 0.244 (±0.326) | 0.362 (±0.428) |
Qwen-2.5-32B | 0.979 (±0.030) | 0.982 (±0.028) | 0.603 (±0.471) | 0.992 (±0.080) | 1.000 (±0.000) | 0.800 (±0.400) | 0.603 (±0.391) | 0.651 (±0.388) | 0.826 (±0.341) |
Qwen-2.5-3B | 0.718 (±0.410) | 0.857 (±0.292) | 0.374 (±0.434) | 0.733 (±0.431) | 0.803 (±0.384) | 0.453 (±0.451) | 0.407 (±0.395) | 0.479 (±0.394) | 0.603 (±0.441) |
Qwen-2.5-72B | 0.871 (±0.317) | 0.987 (±0.025) | 0.614 (±0.471) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.731 (±0.369) | 0.811 (±0.329) | 0.877 (±0.300) |
Qwen-2.0-57B-A14B | 0.741 (±0.399) | 0.932 (±0.173) | 0.222 (±0.370) | 0.860 (±0.345) | 0.895 (±0.307) | 0.630 (±0.438) | 0.510 (±0.399) | 0.599 (±0.393) | 0.673 (±0.424) |
Qwen-2.5-7B | 0.966 (±0.139) | 0.973 (±0.119) | 0.329 (±0.411) | 0.917 (±0.258) | 0.976 (±0.136) | 0.586 (±0.459) | 0.565 (±0.397) | 0.603 (±0.391) | 0.739 (±0.394) |
Qwen-2.5-Coder-32B | 0.937 (±0.219) | 0.991 (±0.017) | 0.478 (±0.476) | 1.000 (±0.000) | 1.000 (±0.000) | 1.000 (±0.000) | 0.814 (±0.325) | 0.830 (±0.314) | 0.881 (±0.297) |
Qwen-2.0-72B | 0.964 (±0.040) | 0.971 (±0.038) | 0.339 (±0.426) | 0.950 (±0.199) | 1.000 (±0.000) | 1.000 (±0.000) | 0.630 (±0.380) | 0.688 (±0.365) | 0.818 (±0.338) |
Qwen-2.0-7B | 0.566 (±0.452) | 0.739 (±0.405) | 0.232 (±0.305) | 0.799 (±0.397) | 0.836 (±0.365) | 0.573 (±0.476) | 0.298 (±0.359) | 0.369 (±0.389) | 0.551 (±0.452) |
Qwen-3-235B | 0.912 (±0.260) | 0.993 (±0.017) | 0.980 (±0.139) | 0.960 (±0.196) | 0.993 (±0.086) | 1.000 (±0.000) | 0.704 (±0.396) | 0.813 (±0.337) | 0.919 (±0.246) |
Leaderboard for RDF Knowledge Graph(KG) related capabilities of Large Language Models(LLMs) as generated with the LLM-KG-Bench framework.
Results for more than 20 RDF related tasks are collected for more than 40 LLMs. The leaderboard contains summarized results:
- board_combined_scores_short.csv: the most concise summary, listing for each LLM combined scores in the RDF (R) and SPARQL (S) handling categories, estimating read(R) and write(W) capabilities for syntax(syn) and semantic(sem). If a dialogue was tested, the result for the first(1) and best(max) answer is given. board_combined_scores.csv is optimized for automated parsing.
- board_main_scores.csv contains the summarized stats for the most important scores
- board_all_stats.csv contains the summarized stats for all scores of all tasks
The full leaderboard with more explanation can be found at https://aksw.github.io/LLM-KG-Bench-Leaderboard/
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