> ## Documentation Index
> Fetch the complete documentation index at: https://docs.landing.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# JSON Response for Splitting

> Understand the Split JSON response: classified sub-documents and processing metadata.

When you split a document with the [Split API](https://docs.landing.ai/dpt3/split.md), the classified splits and metadata are returned in a structured JSON format.

## Response Structure

The response contains the following top-level fields:

* [`splits`](#splits-array-splits): Array of split objects containing the classified sub-documents.
* [`metadata`](#processing-metadata-metadata): Processing information including credit usage, duration, filename, job ID, page count, and model version.

## Splits Array (`splits`)

The `splits` field contains an array of classified sub-documents. Each split object includes:

* **`classification`**: The Split Type name assigned to this sub-document (for example, "Bank Statement" or "Pay Stub").
* **`identifier`**: The unique identifier value for this split (for example, "2024-01-15" or "Invoice #12345"). This field is `null` if no identifier was specified for this Split Type.
* **`pages`**: Array of zero-indexed page numbers that belong to this split.
* **`markdowns`**: Array of Markdown content strings, one for each page in this split. The order matches the `pages` array.

### Classification and Identifiers

The `classification` field corresponds to the Split Type names you defined in your [Split Rules](https://docs.landing.ai/dpt3/split.md#split-rules). If the API cannot classify a page, it assigns the classification `uncategorized`.

When you specify an identifier in your Split Rules (such as "Date" or "Invoice Number"), the API creates separate splits for each unique identifier value it finds. The `identifier` field contains the extracted value (for example, "2024-01-15" or "INV-001").

### Pages and Markdown Content

The `pages` array lists which pages belong to each split. Pages are zero-indexed, so the first page is `0`. [Parse](https://docs.landing.ai/dpt3/parse-response.md) numbers pages from 1, so page `0` in a split is page 1 in the parse response's `grounding.page`.

The `markdowns` array contains the Markdown content for each page, taken from the Markdown you sent. Each element corresponds to the page at the same index in the `pages` array. For example, if `pages` is `[0, 1, 2]`, then `markdowns[0]` contains the Markdown for page 0, `markdowns[1]` contains the Markdown for page 1, and `markdowns[2]` contains the Markdown for page 2.

## Processing Metadata (`metadata`)

The `metadata` field provides information about the split process:

* **`filename`**: The name of the input Markdown file.
* **`org_id`**: Organization identifier.
* **`page_count`**: Total number of pages in the document.
* **`duration_ms`**: Processing time in milliseconds.
* **`credit_usage`**: Credits consumed, before rounding: the input character count divided by 5,000. The amount billed is this value rounded up to the nearest 0.1 credit. See [Credit Consumption](https://docs.landing.ai/dpt3/credit-consumption.md#split).
* **`job_id`**: Unique job identifier.
* **`version`**: Model version used for splitting.

## Example Response

This example shows a split response for a three-page document containing one bank statement and two pay stubs. The bank statement has no identifier, so its `identifier` is `null`. Each pay stub is identified by its pay date, so the two pay stubs are separate splits even though they share a classification.

```json theme={null}
{
  "splits": [
    {
      "classification": "Bank Statement",
      "identifier": null,
      "pages": [0],
      "markdowns": [
        "## Bank Statement\n\nAccount Number: 1234567890\n\nStatement Period: January 1 - January 31, 2025\n\n| Date | Description | Amount |\n|------|-------------|--------|\n| 01/05 | Deposit | $2,500.00 |\n| 01/12 | Withdrawal | -$500.00 |\n\nEnding Balance: $2,000.00"
      ]
    },
    {
      "classification": "Pay Stub",
      "identifier": "2025-01-15",
      "pages": [1],
      "markdowns": [
        "## Pay Stub\n\nEmployee: John Smith\n\nPay Date: January 15, 2025\n\nGross Pay: $6,000.00\n\nNet Pay: $4,500.00"
      ]
    },
    {
      "classification": "Pay Stub",
      "identifier": "2025-01-30",
      "pages": [2],
      "markdowns": [
        "## Pay Stub\n\nEmployee: John Smith\n\nPay Date: January 30, 2025\n\nGross Pay: $6,000.00\n\nNet Pay: $4,500.00"
      ]
    }
  ],
  "metadata": {
    "filename": "mixed-documents.md",
    "org_id": "org_abc123",
    "page_count": 3,
    "duration_ms": 2145,
    "credit_usage": 0.1006,
    "job_id": "split_xyz789",
    "version": "split-20260903"
  }
}
```


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