Export Content with Entity Annotations

User Intent

"How do I export content with entity annotations? Show me export formats with entity metadata."

Operation

SDK Methods: getContent(), queryContents() for export Format: JSON export with entity data Use Case: Data export with entity annotations

Prerequisites

• Content with extracted entities

• Export destination (file, database)

• Understanding of entity structure

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Complete Code Example (TypeScript)

import { Graphlit } from 'graphlit-client';
import * as fs from 'fs';

const graphlit = new Graphlit();

// Get content with entities
const content = await graphlit.getContent('content-id');

// Prepare export data
const exportData = {
  id: content.content.id,
  name: content.content.name,
  type: content.content.type,
  creationDate: content.content.creationDate,
  text: content.content.markdown,
  
  entities: content.content.observations?.map(obs => ({
    type: obs.type,
    name: obs.observable.name,
    id: obs.observable.id,
    occurrences: obs.occurrences?.map(occ => ({
      confidence: occ.confidence,
      pageIndex: occ.pageIndex,
      boundingBox: occ.boundingBox,
      startTime: occ.startTime,
      endTime: occ.endTime
    }))
  })) || []
};

// Export as JSON
fs.writeFileSync('export.json', JSON.stringify(exportData, null, 2));
console.log('Exported with entity annotations');

// Export as CSV (flattened)
const csvRows = [
  ['Entity Type', 'Entity Name', 'Confidence', 'Page', 'Document'].join(',')
];

content.content.observations?.forEach(obs => {
  obs.occurrences?.forEach(occ => {
    csvRows.push([
      obs.type,
      obs.observable.name,
      occ.confidence.toFixed(2),
      occ.pageIndex?.toString() || '',
      content.content.name
    ].join(','));
  });
});

fs.writeFileSync('export.csv', csvRows.join('\n'));
console.log('Exported as CSV');

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Export Formats

JSON (Full Fidelity)

Complete entity data with occurrences

CSV (Tabular)

Flattened for spreadsheet analysis

XML (Structured)

Hierarchical entity annotations

Database (Structured Storage)

PostgreSQL, MongoDB for querying

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Use Cases

Data Analysis: Export for external tools Backup: Archive with entity data Integration: Feed to other systems Reporting: Generate entity reports Training Data: ML model training

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Developer Hints

• Include entity IDs for re-linking

• Preserve occurrence data (timestamps, pages)

• Export in batches for large datasets

• Compress for large exports

• Include metadata (dates, sources)

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