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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>LLM Benchmark Results</title>
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<div class="container">
<h1>LLM Benchmark Results</h1>
The following page shows the results of <a href="https://github.com/aksw/LLM-KG-Bench" target="_blank">LLM-KG-Bench</a> runs on various models and RDF related benchmark tasks.
Below is an overview based on the <a href="#combined-scores">combined scores</a>, <a href="#main-scores">main task scores</a> and <a href="#capability-compass">capability compass plots</a> for each model.
At the <a href="#downloads">bottom of the page</a> you can find links to download the underlying data as CSV and HTML files.
<h2 id="combined-scores">Combined Scores Overview</h2>
<p class="subtitle">Interactive table showing model combined scores (mean (+- standard deviation)) across several capabilities. Click column headers to sort, or use the search box to filter.</p>
<ul>
<li><strong>R-Syn-1:</strong> RDF-Syntax-Capability on first answer</li>
<li><strong>R-Syn-max:</strong> RDF-Syntax-Capability on best answer</li>
<li><strong>R-Sem:</strong> RDF-Semantics-Capability based on tasks RdfConnectionExplainStatic and RdfFriendCount</li>
<li><strong>S-Syn-1:</strong> SPARQL-Syntax-Capability on first answer</li>
<li><strong>S-Syn-max:</strong> SPARQL-Syntax-Capability on best answer</li>
<li><strong>S-Sem-R:</strong> SPARQL-Semantic-Read-Capability</li>
<li><strong>S-Sem-W-1:</strong> SPARQL-Semantic-Write-Capability on first answer</li>
<li><strong>S-Sem-W-max:</strong> SPARQL-Semantic-Write-Capability on best answer</li>
</ul>
<div class="table-wrap">
<table class="dataframe display cell-border compact stripe" id="benchmarkTable">
<thead>
<tr style="text-align: right;">
<th>Model</th>
<th>total</th>
<th>R-Syn-1</th>
<th>R-Syn-Max</th>
<th>R-Sem</th>
<th>S-Syn-1</th>
<th>S-Syn-Max</th>
<th>S-Sem-R</th>
<th>S-Sem-W-1</th>
<th>S-Sem-W-max</th>
</tr>
</thead>
<tbody>
<tr>
<td>Qwen-3.5-397B</td>
<td>0.977 (±0.133)</td>
<td>0.941 (±0.215)</td>
<td>0.994 (±0.015)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.940 (±0.211)</td>
<td>0.940 (±0.211)</td>
</tr>
<tr>
<td>Claude Opus 4.6</td>
<td>0.896 (±0.270)</td>
<td>0.934 (±0.234)</td>
<td>0.996 (±0.013)</td>
<td>0.657 (±0.415)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.747 (±0.362)</td>
<td>0.837 (±0.311)</td>
</tr>
<tr>
<td>Claude Sonnet 4.6</td>
<td>0.844 (±0.321)</td>
<td>0.934 (±0.234)</td>
<td>0.996 (±0.013)</td>
<td>0.282 (±0.300)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.747 (±0.362)</td>
<td>0.797 (±0.338)</td>
</tr>
<tr>
<td>Gemini 3 Flash Preview</td>
<td>0.942 (±0.200)</td>
<td>0.961 (±0.168)</td>
<td>0.995 (±0.014)</td>
<td>0.973 (±0.061)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.760 (±0.367)</td>
<td>0.850 (±0.312)</td>
</tr>
<tr>
<td>GPT5.2-chat</td>
<td>0.955 (±0.178)</td>
<td>0.962 (±0.168)</td>
<td>0.995 (±0.014)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.807 (±0.332)</td>
<td>0.877 (±0.276)</td>
</tr>
<tr>
<td>GPT5.4 2026/03</td>
<td>0.908 (±0.253)</td>
<td>0.934 (±0.234)</td>
<td>0.996 (±0.013)</td>
<td>0.998 (±0.020)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.647 (±0.388)</td>
<td>0.687 (±0.381)</td>
</tr>
<tr>
<td>Claude 3.5 Haiku</td>
<td>0.925 (±0.232)</td>
<td>0.937 (±0.203)</td>
<td>0.984 (±0.029)</td>
<td>0.779 (±0.395)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.817 (±0.325)</td>
<td>0.887 (±0.266)</td>
</tr>
<tr>
<td>Claude 3.5 Sonnet</td>
<td>0.933 (±0.222)</td>
<td>0.950 (±0.175)</td>
<td>0.990 (±0.022)</td>
<td>0.832 (±0.370)</td>
<td>0.980 (±0.125)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.857 (±0.295)</td>
<td>0.857 (±0.295)</td>
</tr>
<tr>
<td>Deepseek-Coder-33B</td>
<td>0.694 (±0.396)</td>
<td>0.773 (±0.366)</td>
<td>0.882 (±0.269)</td>
<td>0.263 (±0.297)</td>
<td>0.943 (±0.221)</td>
<td>0.984 (±0.112)</td>
<td>0.313 (±0.309)</td>
<td>0.689 (±0.379)</td>
<td>0.703 (±0.374)</td>
</tr>
<tr>
<td>Deepseek-R1</td>
<td>0.931 (±0.226)</td>
<td>0.955 (±0.174)</td>
<td>0.991 (±0.020)</td>
<td>0.992 (±0.089)</td>
<td>0.935 (±0.247)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.746 (±0.382)</td>
<td>0.832 (±0.316)</td>
</tr>
<tr>
<td>Deepseek-Chat-v3</td>
<td>0.848 (±0.326)</td>
<td>0.843 (±0.347)</td>
<td>0.991 (±0.020)</td>
<td>0.591 (±0.466)</td>
<td>0.957 (±0.202)</td>
<td>0.997 (±0.050)</td>
<td>0.923 (±0.214)</td>
<td>0.702 (±0.384)</td>
<td>0.782 (±0.348)</td>
</tr>
<tr>
<td>Gemini 1.5 Flash</td>
<td>0.907 (±0.263)</td>
<td>0.920 (±0.242)</td>
<td>0.983 (±0.028)</td>
<td>0.878 (±0.325)</td>
<td>0.865 (±0.324)</td>
<td>0.910 (±0.272)</td>
<td>1.000 (±0.000)</td>
<td>0.850 (±0.304)</td>
<td>0.850 (±0.304)</td>
</tr>
<tr>
<td>Gemini 1.5 Pro</td>
<td>0.896 (±0.282)</td>
<td>0.887 (±0.291)</td>
<td>0.966 (±0.127)</td>
<td>0.796 (±0.399)</td>
<td>0.845 (±0.339)</td>
<td>0.905 (±0.286)</td>
<td>1.000 (±0.000)</td>
<td>0.883 (±0.276)</td>
<td>0.883 (±0.276)</td>
</tr>
<tr>
<td>Gemini 2.0 Flash Exp</td>
<td>0.895 (±0.260)</td>
<td>0.986 (±0.025)</td>
<td>0.988 (±0.024)</td>
<td>0.931 (±0.197)</td>
<td>0.994 (±0.079)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.604 (±0.394)</td>
<td>0.657 (±0.387)</td>
</tr>
<tr>
<td>Llama-3.1-70B</td>
<td>0.860 (±0.311)</td>
<td>0.908 (±0.234)</td>
<td>0.973 (±0.034)</td>
<td>0.559 (±0.484)</td>
<td>0.997 (±0.050)</td>
<td>0.997 (±0.050)</td>
<td>1.000 (±0.000)</td>
<td>0.694 (±0.381)</td>
<td>0.754 (±0.361)</td>
</tr>
<tr>
<td>Llama-3.1-8B</td>
<td>0.530 (±0.452)</td>
<td>0.779 (±0.375)</td>
<td>0.915 (±0.228)</td>
<td>0.462 (±0.421)</td>
<td>0.401 (±0.475)</td>
<td>0.521 (±0.477)</td>
<td>0.535 (±0.377)</td>
<td>0.273 (±0.401)</td>
<td>0.355 (±0.425)</td>
</tr>
<tr>
<td>Llama-3.2-1B</td>
<td>0.123 (±0.276)</td>
<td>0.250 (±0.366)</td>
<td>0.411 (±0.409)</td>
<td>0.159 (±0.254)</td>
<td>0.026 (±0.143)</td>
<td>0.079 (±0.260)</td>
<td>0.021 (±0.070)</td>
<td>0.010 (±0.050)</td>
<td>0.027 (±0.073)</td>
</tr>
<tr>
<td>Llama-3.2-3B</td>
<td>0.335 (±0.416)</td>
<td>0.402 (±0.452)</td>
<td>0.773 (±0.332)</td>
<td>0.344 (±0.397)</td>
<td>0.196 (±0.374)</td>
<td>0.322 (±0.444)</td>
<td>0.308 (±0.373)</td>
<td>0.120 (±0.256)</td>
<td>0.212 (±0.308)</td>
</tr>
<tr>
<td>Llama-3.3-70B</td>
<td>0.853 (±0.318)</td>
<td>0.975 (±0.032)</td>
<td>0.978 (±0.029)</td>
<td>0.595 (±0.487)</td>
<td>0.985 (±0.122)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.617 (±0.398)</td>
<td>0.671 (±0.385)</td>
</tr>
<tr>
<td>Llama-3.0-70B</td>
<td>0.847 (±0.324)</td>
<td>0.961 (±0.114)</td>
<td>0.974 (±0.033)</td>
<td>0.523 (±0.480)</td>
<td>0.955 (±0.208)</td>
<td>0.990 (±0.099)</td>
<td>1.000 (±0.000)</td>
<td>0.645 (±0.405)</td>
<td>0.731 (±0.367)</td>
</tr>
<tr>
<td>Llama-3.0-8B</td>
<td>0.434 (±0.435)</td>
<td>0.586 (±0.426)</td>
<td>0.632 (±0.416)</td>
<td>0.219 (±0.290)</td>
<td>0.271 (±0.445)</td>
<td>0.425 (±0.488)</td>
<td>0.615 (±0.337)</td>
<td>0.281 (±0.397)</td>
<td>0.445 (±0.417)</td>
</tr>
<tr>
<td>Llama-4-Maverick</td>
<td>0.859 (±0.305)</td>
<td>0.870 (±0.241)</td>
<td>0.974 (±0.033)</td>
<td>0.655 (±0.465)</td>
<td>0.960 (±0.196)</td>
<td>1.000 (±0.000)</td>
<td>0.910 (±0.244)</td>
<td>0.687 (±0.381)</td>
<td>0.815 (±0.327)</td>
</tr>
<tr>
<td>GPT3.5 2024/01</td>
<td>0.800 (±0.356)</td>
<td>0.975 (±0.126)</td>
<td>0.995 (±0.014)</td>
<td>0.411 (±0.442)</td>
<td>0.944 (±0.230)</td>
<td>1.000 (±0.000)</td>
<td>0.696 (±0.374)</td>
<td>0.674 (±0.387)</td>
<td>0.707 (±0.376)</td>
</tr>
<tr>
<td>GPT4o 2024/11</td>
<td>0.902 (±0.244)</td>
<td>0.937 (±0.212)</td>
<td>0.986 (±0.024)</td>
<td>0.726 (±0.377)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.881 (±0.183)</td>
<td>0.817 (±0.325)</td>
<td>0.867 (±0.286)</td>
</tr>
<tr>
<td>GPT4o-mini 2024/07</td>
<td>0.827 (±0.333)</td>
<td>0.919 (±0.232)</td>
<td>0.983 (±0.030)</td>
<td>0.384 (±0.415)</td>
<td>0.921 (±0.246)</td>
<td>0.960 (±0.174)</td>
<td>0.962 (±0.089)</td>
<td>0.709 (±0.385)</td>
<td>0.777 (±0.349)</td>
</tr>
<tr>
<td>GPTo1-mini 2024/09</td>
<td>0.911 (±0.251)</td>
<td>0.835 (±0.351)</td>
<td>0.992 (±0.018)</td>
<td>0.994 (±0.031)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.697 (±0.379)</td>
<td>0.767 (±0.354)</td>
</tr>
<tr>
<td>GPTo1-pre 2024/09</td>
<td>0.889 (±0.268)</td>
<td>0.911 (±0.256)</td>
<td>0.992 (±0.020)</td>
<td>0.658 (±0.373)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.742 (±0.365)</td>
<td>0.812 (±0.329)</td>
</tr>
<tr>
<td>OpenCoder-8B</td>
<td>0.557 (±0.454)</td>
<td>0.746 (±0.405)</td>
<td>0.817 (±0.354)</td>
<td>0.167 (±0.285)</td>
<td>0.622 (±0.482)</td>
<td>0.737 (±0.437)</td>
<td>0.400 (±0.422)</td>
<td>0.459 (±0.422)</td>
<td>0.509 (±0.417)</td>
</tr>
<tr>
<td>Phi-3.5-mini</td>
<td>0.481 (±0.432)</td>
<td>0.608 (±0.412)</td>
<td>0.639 (±0.390)</td>
<td>0.176 (±0.297)</td>
<td>0.637 (±0.466)</td>
<td>0.683 (±0.450)</td>
<td>0.450 (±0.381)</td>
<td>0.309 (±0.367)</td>
<td>0.350 (±0.371)</td>
</tr>
<tr>
<td>Phi-3.5-MoE</td>
<td>0.738 (±0.359)</td>
<td>0.831 (±0.296)</td>
<td>0.841 (±0.287)</td>
<td>0.517 (±0.421)</td>
<td>0.808 (±0.391)</td>
<td>0.932 (±0.238)</td>
<td>0.688 (±0.185)</td>
<td>0.637 (±0.394)</td>
<td>0.648 (±0.389)</td>
</tr>
<tr>
<td>Phi-3.0-medium-128k</td>
<td>0.561 (±0.439)</td>
<td>0.838 (±0.318)</td>
<td>0.886 (±0.257)</td>
<td>0.248 (±0.364)</td>
<td>0.547 (±0.475)</td>
<td>0.603 (±0.466)</td>
<td>0.625 (±0.316)</td>
<td>0.360 (±0.412)</td>
<td>0.385 (±0.417)</td>
</tr>
<tr>
<td>Phi-3.0-mini-128k</td>
<td>0.431 (±0.415)</td>
<td>0.582 (±0.424)</td>
<td>0.660 (±0.388)</td>
<td>0.263 (±0.333)</td>
<td>0.486 (±0.479)</td>
<td>0.549 (±0.480)</td>
<td>0.428 (±0.336)</td>
<td>0.231 (±0.291)</td>
<td>0.245 (±0.292)</td>
</tr>
<tr>
<td>Phi-3.0-small-128k</td>
<td>0.374 (±0.413)</td>
<td>0.346 (±0.394)</td>
<td>0.432 (±0.385)</td>
<td>0.284 (±0.364)</td>
<td>0.366 (±0.427)</td>
<td>0.394 (±0.429)</td>
<td>0.593 (±0.487)</td>
<td>0.278 (±0.352)</td>
<td>0.300 (±0.356)</td>
</tr>
<tr>
<td>Qwen-2.0-0.5B</td>
<td>0.038 (±0.138)</td>
<td>0.068 (±0.159)</td>
<td>0.076 (±0.171)</td>
<td>0.085 (±0.205)</td>
<td>0.005 (±0.071)</td>
<td>0.012 (±0.111)</td>
<td>0.040 (±0.136)</td>
<td>0.006 (±0.072)</td>
<td>0.010 (±0.080)</td>
</tr>
<tr>
<td>Qwen-2.0-1.5B</td>
<td>0.189 (±0.332)</td>
<td>0.126 (±0.294)</td>
<td>0.145 (±0.314)</td>
<td>0.222 (±0.349)</td>
<td>0.293 (±0.448)</td>
<td>0.351 (±0.465)</td>
<td>0.154 (±0.196)</td>
<td>0.105 (±0.177)</td>
<td>0.115 (±0.182)</td>
</tr>
<tr>
<td>Qwen-2.5-0.5B</td>
<td>0.097 (±0.244)</td>
<td>0.053 (±0.153)</td>
<td>0.101 (±0.235)</td>
<td>0.083 (±0.199)</td>
<td>0.157 (±0.360)</td>
<td>0.185 (±0.384)</td>
<td>0.071 (±0.179)</td>
<td>0.061 (±0.128)</td>
<td>0.064 (±0.129)</td>
</tr>
<tr>
<td>Qwen-2.5-14B</td>
<td>0.763 (±0.390)</td>
<td>0.781 (±0.393)</td>
<td>0.922 (±0.245)</td>
<td>0.331 (±0.432)</td>
<td>0.897 (±0.303)</td>
<td>0.910 (±0.286)</td>
<td>0.933 (±0.240)</td>
<td>0.658 (±0.378)</td>
<td>0.671 (±0.374)</td>
</tr>
<tr>
<td>Qwen-2.5-1.5B</td>
<td>0.362 (±0.428)</td>
<td>0.470 (±0.459)</td>
<td>0.584 (±0.452)</td>
<td>0.266 (±0.339)</td>
<td>0.494 (±0.485)</td>
<td>0.527 (±0.482)</td>
<td>0.127 (±0.268)</td>
<td>0.186 (±0.272)</td>
<td>0.244 (±0.326)</td>
</tr>
<tr>
<td>Qwen-2.5-32B</td>
<td>0.826 (±0.341)</td>
<td>0.979 (±0.030)</td>
<td>0.982 (±0.028)</td>
<td>0.603 (±0.471)</td>
<td>0.992 (±0.080)</td>
<td>1.000 (±0.000)</td>
<td>0.800 (±0.400)</td>
<td>0.603 (±0.391)</td>
<td>0.651 (±0.388)</td>
</tr>
<tr>
<td>Qwen-2.5-3B</td>
<td>0.603 (±0.441)</td>
<td>0.718 (±0.410)</td>
<td>0.857 (±0.292)</td>
<td>0.374 (±0.434)</td>
<td>0.733 (±0.431)</td>
<td>0.803 (±0.384)</td>
<td>0.453 (±0.451)</td>
<td>0.407 (±0.395)</td>
<td>0.479 (±0.394)</td>
</tr>
<tr>
<td>Qwen-2.5-72B</td>
<td>0.877 (±0.300)</td>
<td>0.871 (±0.317)</td>
<td>0.987 (±0.025)</td>
<td>0.614 (±0.471)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.731 (±0.369)</td>
<td>0.811 (±0.329)</td>
</tr>
<tr>
<td>Qwen-2.0-57B-A14B</td>
<td>0.673 (±0.424)</td>
<td>0.741 (±0.399)</td>
<td>0.932 (±0.173)</td>
<td>0.222 (±0.370)</td>
<td>0.860 (±0.345)</td>
<td>0.895 (±0.307)</td>
<td>0.630 (±0.438)</td>
<td>0.510 (±0.399)</td>
<td>0.599 (±0.393)</td>
</tr>
<tr>
<td>Qwen-2.5-7B</td>
<td>0.739 (±0.394)</td>
<td>0.966 (±0.139)</td>
<td>0.973 (±0.119)</td>
<td>0.329 (±0.411)</td>
<td>0.917 (±0.258)</td>
<td>0.976 (±0.136)</td>
<td>0.586 (±0.459)</td>
<td>0.565 (±0.397)</td>
<td>0.603 (±0.391)</td>
</tr>
<tr>
<td>Qwen-2.5-Coder-32B</td>
<td>0.881 (±0.297)</td>
<td>0.937 (±0.219)</td>
<td>0.991 (±0.017)</td>
<td>0.478 (±0.476)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.814 (±0.325)</td>
<td>0.830 (±0.314)</td>
</tr>
<tr>
<td>Qwen-2.0-72B</td>
<td>0.818 (±0.338)</td>
<td>0.964 (±0.040)</td>
<td>0.971 (±0.038)</td>
<td>0.339 (±0.426)</td>
<td>0.950 (±0.199)</td>
<td>1.000 (±0.000)</td>
<td>1.000 (±0.000)</td>
<td>0.630 (±0.380)</td>
<td>0.688 (±0.365)</td>
</tr>
<tr>
<td>Qwen-2.0-7B</td>
<td>0.551 (±0.452)</td>
<td>0.566 (±0.452)</td>
<td>0.739 (±0.405)</td>
<td>0.232 (±0.305)</td>
<td>0.799 (±0.397)</td>
<td>0.836 (±0.365)</td>
<td>0.573 (±0.476)</td>
<td>0.298 (±0.359)</td>
<td>0.369 (±0.389)</td>
</tr>
<tr>
<td>Qwen-3-235B</td>
<td>0.919 (±0.246)</td>
<td>0.912 (±0.260)</td>
<td>0.993 (±0.017)</td>
<td>0.980 (±0.139)</td>
<td>0.960 (±0.196)</td>
<td>0.993 (±0.086)</td>
<td>1.000 (±0.000)</td>
<td>0.704 (±0.396)</td>
<td>0.813 (±0.337)</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="container" style="margin-top: 40px;">
<h2 id="main-scores">Main Scores for all Benchmark Tasks</h2>
<p class="subtitle">This table provides a detailed breakdown showing the average main score for each benchmark task for each model.</p>
<div class="table-wrap">
<table class="dataframe display cell-border compact stripe" id="mainScoresTable">
<thead>
<tr style="text-align: right;">
<th>Model</th>
<th>RdfConnectionExplainStatic-jsonld (listTrimF1)</th>
<th>RdfConnectionExplainStatic-nt (listTrimF1)</th>
<th>RdfConnectionExplainStatic-turtle (listTrimF1)</th>
<th>RdfConnectionExplainStatic-xml (listTrimF1)</th>
<th>RdfFriendCount-jsonld-1 (f1)</th>
<th>RdfFriendCount-jsonld-2 (f1)</th>
<th>RdfFriendCount-nt-1 (f1)</th>
<th>RdfFriendCount-nt-2 (f1)</th>
<th>RdfFriendCount-turtle-1 (f1)</th>
<th>RdfFriendCount-turtle-2 (f1)</th>
<th>RdfFriendCount-xml-1 (f1)</th>
<th>RdfFriendCount-xml-2 (f1)</th>
<th>RdfSyntaxFixList-jsonld (max_combined)</th>
<th>RdfSyntaxFixList-nt (max_combined)</th>
<th>RdfSyntaxFixList-turtle (max_combined)</th>
<th>Sparql2AnswerListOrga-jsonld (combinedF1)</th>
<th>Sparql2AnswerListOrga-turtle (combinedF1)</th>
<th>SparqlSyntaxFixingListLcQuad (max_combined)</th>
<th>Text2AnswerListOrga-jsonld (combinedF1)</th>
<th>Text2AnswerListOrga-turtle (combinedF1)</th>
<th>Text2SparqlExecEvalListBeastiary-turtle-schema (max_combined)</th>
<th>Text2SparqlExecEvalListBeastiary-turtle-subgraph (max_combined)</th>
<th>Text2SparqlExecEvalListBeastiary-turtle-subschema (max_combined)</th>
<th>Text2SparqlExecEvalListCoypuMini (max_combined)</th>
<th>Text2SparqlExecEvalListOrgaNumerical (max_combined)</th>
<th>Text2SparqlExecEvalListOrganizational (max_combined)</th>
</tr>
</thead>
<tbody>
<tr>
<td>Claude 3.5 Haiku</td>
<td>1.000</td>
<td>0.903</td>
<td>0.889</td>
<td>0.995</td>
<td>0.000</td>
<td>0.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.979</td>
<td>0.997</td>
<td>0.975</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.938</td>
<td>0.850</td>
<td>0.373</td>
<td>0.947</td>
<td>0.307</td>
<td>0.600</td>
<td>1.000</td>
<td>1.000</td>
</tr>
<tr>
<td>Claude 3.5 Sonnet</td>
<td>1.000</td>
<td>0.972</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.100</td>
<td>0.300</td>
<td>0.950</td>
<td>1.000</td>
<td>0.550</td>
<td>1.000</td>
<td>0.989</td>
<td>0.997</td>
<td>0.984</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.411</td>
<td>0.947</td>
<td>0.427</td>
<td>0.520</td>
<td>0.960</td>
<td>1.000</td>
</tr>
<tr>
<td>Claude Opus 4.6</td>
<td>0.958</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.095</td>
<td>0.095</td>
<td>0.219</td>
<td>0.204</td>
<td>1.000</td>
<td>1.000</td>
<td>0.149</td>
<td>0.103</td>
<td>0.989</td>
<td>0.999</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.787</td>
<td>0.947</td>
<td>0.667</td>
<td>0.600</td>
<td>0.960</td>
<td>0.840</td>
</tr>
<tr>
<td>Claude Sonnet 4.6</td>
<td>0.456</td>
<td>0.548</td>
<td>0.456</td>
<td>0.893</td>
<td>0.092</td>
<td>0.092</td>
<td>0.052</td>
<td>0.048</td>
<td>0.091</td>
<td>0.091</td>
<td>0.092</td>
<td>0.092</td>
<td>0.989</td>
<td>0.997</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.709</td>
<td>0.947</td>
<td>0.747</td>
<td>0.600</td>
<td>0.840</td>
<td>0.800</td>
</tr>
<tr>
<td>Deepseek-Chat-v3</td>
<td>0.989</td>
<td>0.856</td>
<td>0.896</td>
<td>0.980</td>
<td>0.293</td>
<td>0.396</td>
<td>0.250</td>
<td>0.309</td>
<td>0.544</td>
<td>0.394</td>
<td>0.514</td>
<td>0.534</td>
<td>0.989</td>
<td>0.993</td>
<td>0.991</td>
<td>0.993</td>
<td>0.922</td>
<td>1.000</td>
<td>0.905</td>
<td>0.713</td>
<td>0.456</td>
<td>0.947</td>
<td>0.408</td>
<td>0.520</td>
<td>0.680</td>
<td>0.980</td>
</tr>
<tr>
<td>Deepseek-Coder-33B</td>
<td>0.529</td>
<td>0.241</td>
<td>0.438</td>
<td>0.447</td>
<td>0.204</td>
<td>0.334</td>
<td>0.111</td>
<td>0.172</td>
<td>0.068</td>
<td>0.083</td>
<td>0.349</td>
<td>0.382</td>
<td>0.976</td>
<td>0.829</td>
<td>0.841</td>
<td>0.224</td>
<td>0.313</td>
<td>0.968</td>
<td>0.228</td>
<td>0.221</td>
<td>0.337</td>
<td>0.915</td>
<td>0.399</td>
<td>0.575</td>
<td>0.571</td>
<td>0.752</td>
</tr>
<tr>
<td>Deepseek-R1</td>
<td>0.960</td>
<td>0.997</td>
<td>1.000</td>
<td>0.980</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.980</td>
<td>1.000</td>
<td>1.000</td>
<td>1.000</td>
<td>0.989</td>
<td>0.997</td>
<td>0.987</td>
<td>0.993</td>
<td>1.000</td>
<td>1.000</td>
<td>0.970</td>
<td>0.985</td>
<td>0.443</td>
<td>0.952</td>
<td>0.349</td>
<td>0.520</td>
<td>0.872</td>
<td>0.984</td>
</tr>
<tr>
<td>GPT3.5 2024/01</td>
<td>0.901</td>
<td>0.801</td>
<td>0.848</td>
<td>0.813</td>
<td>0.200</td>
<td>0.550</td>
<td>0.000</td>
<td>0.000</td>
<td>0.000</td>
<td>0.000</td>
<td>0.550</td>
<td>0.900</td>
<td>0.989</td>
<td>0.998</td>
<td>0.997</td>
<td>0.500</td>
<td>0.696</td>
<td>1.000</td>
<td>0.506</td>
<td>0.850</td>
<td>0.387</td>
<td>0.947</td>
<td>0.261</td>
<td>0.520</td>
<td>0.600</td>
<td>0.760</td>
</tr>
<tr>
<td>GPT4o 2024/11</td>
<td>0.850</td>
<td>0.598</td>
<td>0.867</td>
<td>0.845</td>
<td>1.000</td>
<td>1.000</td>
<td>0.000</td>
<td>0.100</td>
<td>1.000</td>
<td>1.000</td>
<td>0.000</td>
<td>1.000</td>
<td>0.989</td>
<td>0.997</td>
<td>0.972</td>
<td>0.950</td>
<td>0.881</td>
<td>1.000</td>
<td>0.950</td>
<td>0.950</td>
<td>0.307</td>
<td>0.947</td>
<td>0.307</td>
<td>0.520</td>
<td>1.000</td>
<td>1.000</td>
</tr>
<tr>
<td>GPT4o-mini 2024/07</td>
<td>0.833</td>
<td>0.723</td>
<td>0.828</td>
<td>0.753</td>
<td>0.100</td>
<td>0.000</td>
<td>0.000</td>
<td>0.150</td>
<td>0.200</td>
<td>0.250</td>
<td>1.000</td>
<td>1.000</td>
<td>0.979</td>
<td>0.995</td>
<td>0.977</td>
<td>0.758</td>
<td>0.962</td>
<td>0.920</td>
<td>0.775</td>