> For the complete documentation index, see [llms.txt](https://docs.apryse.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.apryse.com/core/smart-data-extraction/document-structure.md).

# Document Structure Recognition

Apryse's Document Structure Recognition engine helps you capture the visual and logical layout of a document. Great for use with Accessibility tagging (e.g., reading order), screen reading tools, docu

{% hint style="info" %}
**Requirements**

*These packages are required to use these features in production. Trial keys have unlimited access to all features*

<a href="https://apryse.com/capabilities#SmartDataExtraction" class="button primary">Package: Smart Data Extraction</a><a href="/core/learn-more/modules.md#data-extraction-module" class="button primary">Module: Data Extraction</a><a href="https://showcase.apryse.com/document-structure-extraction" class="button primary">Live demo</a>
{% endhint %}

## Document Structure Recognition

Apryse's Document Structure Recognition engine helps you capture the visual and logical layout of a document. Unlike tabular extraction, this mode is designed to mimic how a human sees the page — recognizing paragraphs, lists, headers, footers, and images as distinct blocks.

It's ideal for use cases involving:

* Accessibility tagging (e.g., reading order)
* Screen reading tools
* Document reconstruction
* Visual layout parsing

### How It Works

The engine detects layout elements based on visual positioning, spacing, indentation, and structural boundaries. It separates:

* Paragraphs and lists
* Headers and footers
* Section columns vs table columns
* Tables embedded inside paragraphs
* Images and graphical elements

### JSON Output Specification

Refer to the following specifications to learn more about the output JSON format:

* [JSON Specification for Tabular Data and Document Structure](https://sdk.apryse.com/api/structurejson/index.html)

### Extract document structure as JSON file

Specify the name of the input PDF file and the name of the output JSON file, then select the Doc Structure engine:

{% tabs %}
{% tab title="C#" %}
{% code lineNumbers="true" %}

```csharp
DataExtractionModule.ExtractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModule.DataExtractionEngine.e_doc_structure);
```

{% endcode %}
{% endtab %}

{% tab title="C++" %}
{% code lineNumbers="true" %}

```cpp
DataExtractionModule::ExtractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModule::e_DocStructure);
```

{% endcode %}
{% endtab %}

{% tab title="Go" %}
{% code lineNumbers="true" %}

```go
DataExtractionModuleExtractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModuleE_DocStructure)
```

{% endcode %}
{% endtab %}

{% tab title="Java" %}
{% code lineNumbers="true" %}

```java
DataExtractionModule.extractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModule.DataExtractionEngine.e_doc_structure);
```

{% endcode %}
{% endtab %}

{% tab title="JavaScript" %}
{% code lineNumbers="true" %}

```js
await PDFNet.DataExtractionModule.extractData('paragraphs_and_tables.pdf', 'paragraphs_and_tables.json', PDFNet.DataExtractionModule.DataExtractionEngine.e_DocStructure);
```

{% endcode %}
{% endtab %}

{% tab title="PHP" %}
{% code lineNumbers="true" %}

```php
DataExtractionModule::ExtractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModule::e_DocStructure);
```

{% endcode %}
{% endtab %}

{% tab title="Python" %}
{% code lineNumbers="true" %}

```python
DataExtractionModule.ExtractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModule.e_DocStructure)
```

{% endcode %}
{% endtab %}

{% tab title="Ruby" %}
{% code lineNumbers="true" %}

```ruby
DataExtractionModule.ExtractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModule::E_DocStructure)
```

{% endcode %}
{% endtab %}

{% tab title="VB" %}
{% code lineNumbers="true" %}

```vb
DataExtractionModule.ExtractData("paragraphs_and_tables.pdf", "paragraphs_and_tables.json", DataExtractionModule.DataExtractionEngine.e_doc_structure)
```

{% endcode %}
{% endtab %}
{% endtabs %}

### Extract document structure as JSON string

If you are going to parse the JSON right away, you may as well retrieve it as an in-memory string, instead of an external file.

Specify the name of the input PDF file, then select the Doc Structure engine:

{% tabs %}
{% tab title="C#" %}
{% code lineNumbers="true" %}

```csharp
string json = DataExtractionModule.ExtractData("tagged.pdf", DataExtractionModule.DataExtractionEngine.e_doc_structure);
```

{% endcode %}
{% endtab %}

{% tab title="C++" %}
{% code lineNumbers="true" %}

```cpp
UString json = DataExtractionModule::ExtractData("tagged.pdf", DataExtractionModule::e_DocStructure);
```

{% endcode %}
{% endtab %}

{% tab title="Go" %}
{% code lineNumbers="true" %}

```go
json := DataExtractionModuleExtractData("tagged.pdf", DataExtractionModuleE_DocStructure).(string)
```

{% endcode %}
{% endtab %}

{% tab title="Java" %}
{% code lineNumbers="true" %}

```java
String json = DataExtractionModule.extractData("tagged.pdf", DataExtractionModule.DataExtractionEngine.e_doc_structure);
```

{% endcode %}
{% endtab %}

{% tab title="JavaScript" %}
{% code lineNumbers="true" %}

```js
const json = await PDFNet.DataExtractionModule.extractDataAsString('tagged.pdf', PDFNet.DataExtractionModule.DataExtractionEngine.e_DocStructure);
```

{% endcode %}
{% endtab %}

{% tab title="PHP" %}
{% code lineNumbers="true" %}

```php
$json = DataExtractionModule::ExtractData("tagged.pdf", DataExtractionModule::e_DocStructure);
```

{% endcode %}
{% endtab %}

{% tab title="Python" %}
{% code lineNumbers="true" %}

```python
json = DataExtractionModule.ExtractData("tagged.pdf", DataExtractionModule.e_DocStructure)
```

{% endcode %}
{% endtab %}

{% tab title="Ruby" %}
{% code lineNumbers="true" %}

```ruby
json = DataExtractionModule.ExtractData("tagged.pdf", DataExtractionModule::E_DocStructure)
```

{% endcode %}
{% endtab %}

{% tab title="VB" %}
{% code lineNumbers="true" %}

```vb
Dim json As String = DataExtractionModule.ExtractData("tagged.pdf", DataExtractionModule.DataExtractionEngine.e_doc_structure)
```

{% endcode %}
{% endtab %}
{% endtabs %}

### Optional Configurations

[Select OCR Language](/core/smart-data-extraction/workflow.md#select-ocr-language)

[Password-Protected PDFs](/core/smart-data-extraction/workflow.md#specify-pdf-password)

[Page Range](/core/smart-data-extraction/workflow.md#select-a-page-range)

[Deep Learning Assist](/core/smart-data-extraction/workflow.md#deep-learning-assist)


---

# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.apryse.com/core/smart-data-extraction/document-structure.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
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