Table parsing from document

Extract a table from a document and return it in a structured format (e.g., HTML).

You can query a model directly and test the results returned when using different parameter values with the Cloud console, or by calling the Vertex AI API directly.

Prompt Freeform

salary_table.pdf

Prompt image

What is the HTML code of the table in this document?

Response

<div>
  <h2>Salary Table 2023-GS</h2>
  <p>Incorporating the 4.1% General Schedule Increase</p>
  <p>Effective January 2023</p>
  <p>Annual Rates by Grade and Step</p>
</div>
<table>
  <thead>
    <tr>
      <th>Grade</th>
      <th>Step 1</th>
      <th>Step 2</th>
      <th>Step 3</th>
      <th>Step 4</th>
      <th>Step 5</th>
      <th>Step 6</th>
      <th>Step 7</th>
      <th>Step 8</th>
      <th>Step 9</th>
      <th>Step 10</th>
      <th>WITHIN GRADE AMOUNTS</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>1</td>
      <td>$ 20,999</td>
      <td>$ 21,704</td>
      <td>$ 22,401</td>
      <td>$ 23,097</td>
      <td>$ 23,794</td>
      <td>$ 24,202</td>
      <td>$ 24,893</td>
      <td>$ 25,589</td>
      <td>$ 25,617</td>
      <td>$ 26,273</td>
      <td>VARIES</td>
    </tr>
    <tr>
      <td>2</td>
      <td>$ 23,612</td>
      <td>$ 24,174</td>
      <td>$ 24,956</td>
      <td>$ 25,617</td>
      <td>$ 25,906</td>
      <td>$ 26,668</td>
      <td>$ 27,430</td>
      <td>$ 28,192</td>
      <td>$ 28,954</td>
      <td>$ 29,716</td>
      <td>VARIES</td>
    </tr>
    <tr>
      <td>3</td>
      <td>$ 25,764</td>
      <td>$ 26,623</td>
      <td>$ 27,482</td>
      <td>$ 28,341</td>
      <td>$ 29,200</td>
      <td>$ 30,059</td>
      <td>$ 30,918</td>
      <td>$ 31,777</td>
      <td>$ 32,636</td>
      <td>$ 33,495</td>
      <td>859</td>
    </tr>
    <tr>
      <td>4</td>
      <td>$ 28,921</td>
      <td>$ 29,885</td>
      <td>$ 30,849</td>
      <td>$ 31,813</td>
      <td>$ 32,777</td>
      <td>$ 33,741</td>
      <td>$ 34,705</td>
      <td>$ 35,669</td>
      <td>$ 36,633</td>
      <td>$ 37,597</td>
      <td>964</td>
    </tr>
    <tr>
      <td>5</td>
      <td>$ 32,357</td>
      <td>$ 33,436</td>
      <td>$ 34,515</td>
      <td>$ 35,594</td>
      <td>$ 36,673</td>
      <td>$ 37,752</td>
      <td>$ 38,831</td>
      <td>$ 39,910</td>
      <td>$ 40,989</td>
      <td>$ 42,068</td>
      <td>1,079</td>
    </tr>
    <tr>
      <td>6</td>
      <td>$ 36,070</td>
      <td>$ 37,272</td>
      <td>$ 38,474</td>
      <td>$ 39,676</td>
      <td>$ 40,878</td>
      <td>$ 42,080</td>
      <td>$ 43,282</td>
      <td>$ 44,484</td>
      <td>$ 45,686</td>
      <td>$ 46,888</td>
      <td>1,202</td>
    </tr>
    <tr>
      <td>7</td>
      <td>$ 40,082</td>
      <td>$ 41,418</td>
      <td>$ 42,754</td>
      <td>$ 44,090</td>
      <td>$ 45,426</td>
      <td>$ 46,762</td>
      <td>$ 48,098</td>
      <td>$ 49,434</td>
      <td>$ 50,770</td>
      <td>$ 52,106</td>
      <td>1,336</td>
    </tr>
    <tr>
      <td>8</td>
      <td>$ 44,389</td>
      <td>$ 45,869</td>
      <td>$ 47,349</td>
      <td>$ 48,829</td>
      <td>$ 50,309</td>
      <td>$ 51,789</td>
      <td>$ 53,269</td>
      <td>$ 54,749</td>
      <td>$ 56,229</td>
      <td>$ 57,709</td>
      <td>1,480</td>
    </tr>
    <tr>
      <td>9</td>
      <td>$ 49,028</td>
      <td>$ 50,662</td>
      <td>$ 52,296</td>
      <td>$ 53,930</td>
      <td>$ 55,564</td>
      <td>$ 57,198</td>
      <td>$ 58,832</td>
      <td>$ 60,466</td>
      <td>$ 62,100</td>
      <td>$ 63,734</td>
      <td>1,634</td>
    </tr>
    <tr>
      <td>10</td>
      <td>$ 53,990</td>
      <td>$ 55,790</td>
      <td>$ 57,590</td>
      <td>$ 59,390</td>
      <td>$ 61,190</td>
      <td>$ 62,990</td>
      <td>$ 64,790</td>
      <td>$ 66,590</td>
      <td>$ 68,390</td>
      <td>$ 70,190</td>
      <td>1,800</td>
    </tr>
    <tr>
      <td>11</td>
      <td>$ 59,319</td>
      <td>$ 61,296</td>
      <td>$ 63,273</td>
      <td>$ 65,250</td>
      <td>$ 67,227</td>
      <td>$ 69,204</td>
      <td>$ 71,181</td>
      <td>$ 73,158</td>
      <td>$ 75,135</td>
      <td>$ 77,112</td>
      <td>1,977</td>
    </tr>
    <tr>
      <td>12</td>
      <td>$ 71,099</td>
      <td>$ 73,469</td>
      <td>$ 75,839</td>
      <td>$ 78,209</td>
      <td>$ 80,579</td>
      <td>$ 82,949</td>
      <td>$ 85,319</td>
      <td>$ 87,689</td>
      <td>$ 90,059</td>
      <td>$ 92,429</td>
      <td>2,370</td>
    </tr>
    <tr>
      <td>13</td>
      <td>$ 84,546</td>
      <td>$ 87,364</td>
      <td>$ 90,182</td>
      <td>$ 93,000</td>
      <td>$ 95,818</td>
      <td>$ 98,636</td>
      <td>$ 101,454</td>
      <td>$ 104,272</td>
      <td>$ 107,090</td>
      <td>$ 109,908</td>
      <td>2,818</td>
    </tr>
    <tr>
      <td>14</td>
      <td>$ 99,908</td>
      <td>$ 103,238</td>
      <td>$ 106,568</td>
      <td>$ 109,898</td>
      <td>$ 113,228</td>
      <td>$ 116,558</td>
      <td>$ 119,888</td>
      <td>$ 123,218</td>
      <td>$ 126,548</td>
      <td>$ 129,878</td>
      <td>3,330</td>
    </tr>
    <tr>
      <td>15</td>
      <td>$ 117,518</td>
      <td>$ 121,435</td>
      <td>$ 125,352</td>
      <td>$ 129,269</td>
      <td>$ 133,186</td>
      <td>$ 137,103</td>
      <td>$ 141,020</td>
      <td>$ 144,937</td>
      <td>$ 148,854</td>
      <td>$ 152,771</td>
      <td>3,917</td>
    </tr>
  </tbody>
</table>
Model: gemini-2.5-pro
Temperature: 0.2
Max output tokens: 8192
TopK: 40.0
TopP: 0.95