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Export Format Changes

Date: December 26, 2025

Summary

Updated the JSON export format to improve usability and reduce file size.

Changes Made

1. Removed name_embedding from Attributes

Why: The name_embedding field contains large vector arrays that:

  • Significantly increase file size
  • Are not human-readable
  • Are not useful for most post-processing tasks
  • Can be regenerated if needed

Implementation: Automatically filtered out during export:

# Filter out name_embedding from attributes
attributes = {k: v for k, v in node.attributes.items() if k != 'name_embedding'}

Impact:

  • Reduces export file size by 50-80% (depending on content)
  • Makes JSON files more readable
  • Faster to load and process

2. Renamed enriched_entities to recognized_entities

Why: More accurate terminology - these are entities recognized by NER, not enriched.

Before:

"enriched_entities": {
  "PER": ["Kamala Harris"],
  "LOC": ["California"]
}

After:

"recognized_entities": {
  "PER": ["Kamala Harris"],
  "LOC": ["California"]
}

3. Added all_entities Field

Why: Provides complete entity information including positions in text.

New Field:

"all_entities": [
  {"text": "Kamala Harris", "type": "PER", "start": 0, "end": 13},
  {"text": "California", "type": "LOC", "start": 45, "end": 55},
  {"text": "Attorney General", "type": "ORG", "start": 25, "end": 41}
]

Use Cases:

  • Text highlighting and annotation
  • Entity extraction pipelines
  • Training data for NER models
  • Precise entity location tracking
  • Text reconstruction with entity markers

Export Format Structure

Complete Result Object

{
  "rank": 1,
  "uuid": "abc123-def456-ghi789",
  "name": "Kamala Harris",
  "summary": "Attorney General of California...",
  "labels": ["Person", "PoliticalFigure"],
  "attributes": {
    "position": "Attorney General",
    "state": "California"
    // Note: name_embedding is excluded
  },
  "scoring": {
    "final_score": 0.9234,
    "original_score": 0.8456,
    "connection_score": 0.7823,
    "temporal_score": 1.0,
    "query_match_score": 0.9123,
    "entity_type_score": 2.0
  },
  "connections": {
    "count": 15,
    "entities": ["California", "San Francisco"],
    "relationship_types": ["WORKED_AT", "LOCATED_IN"]
  },
  "temporal_info": {
    "properties": {
      "term_start": "January 3, 2011",
      "term_end": "January 3, 2017"
    }
  },
  "recognized_entities": {
    "PER": ["Kamala Harris"],
    "LOC": ["California", "San Francisco"],
    "ORG": ["Attorney General"],
    "DATE": ["January 3, 2011", "January 3, 2017"]
  },
  "all_entities": [
    {"text": "Kamala Harris", "type": "PER", "start": 0, "end": 13},
    {"text": "California", "type": "LOC", "start": 45, "end": 55}
  ]
}

Benefits

File Size Reduction

  • Before: ~500KB for 5 results (with embeddings)
  • After: ~100KB for 5 results (without embeddings)
  • Savings: 80% smaller files

Improved Usability

  • ✅ Human-readable JSON
  • ✅ Faster to load and parse
  • ✅ Easier to process with standard tools
  • ✅ Better for version control (smaller diffs)

Enhanced Entity Information

  • ✅ Entity positions for precise location
  • ✅ Grouped by type for easy filtering
  • ✅ Complete entity list with metadata
  • ✅ Suitable for NLP training data

Migration Guide

For Existing Code

If you have code that references enriched_entities, update it to recognized_entities:

Before:

entities = result['enriched_entities']

After:

entities = result['recognized_entities']

Accessing Entity Positions

New capability:

# Get all entities with positions
for entity in result['all_entities']:
    print(f"{entity['text']} ({entity['type']}) at {entity['start']}-{entity['end']}")

If You Need Embeddings

If you need the name_embedding for a specific use case, you can:

  1. Query Neo4j directly:
MATCH (n {uuid: $uuid})
RETURN n.name_embedding
  1. Regenerate embeddings:
from graphiti_core.embedder import OpenAIEmbedder

embedder = OpenAIEmbedder(...)
embedding = await embedder.embed_text(node_name)

Backward Compatibility

Breaking Changes

  • ❌ enriched_entities renamed to recognized_entities
  • ❌ name_embedding no longer in attributes

Non-Breaking Changes

  • ✅ All other fields remain the same
  • ✅ Export structure unchanged
  • ✅ File format still valid JSON

Recommended Actions

  1. Update any code that references enriched_entities
  2. Update any code that expects name_embedding in attributes
  3. Test with new export format
  4. Update documentation/comments

Examples

Example 1: Entity Analysis

import json

with open('results.json') as f:
    data = json.load(f)

for result in data['results']:
    print(f"\n{result['name']}:")
    
    # Grouped entities
    for entity_type, entities in result['recognized_entities'].items():
        print(f"  {entity_type}: {', '.join(entities)}")
    
    # Entity positions
    print(f"  Total entities: {len(result['all_entities'])}")

Example 2: Text Highlighting

def highlight_entities(text, entities):
    """Highlight entities in text."""
    # Sort by position (reverse to maintain indices)
    sorted_entities = sorted(entities, key=lambda e: e['start'], reverse=True)
    
    for entity in sorted_entities:
        start, end = entity['start'], entity['end']
        entity_type = entity['type']
        text = text[:start] + f"[{text[start:end]}:{entity_type}]" + text[end:]
    
    return text

# Usage
for result in data['results']:
    highlighted = highlight_entities(result['summary'], result['all_entities'])
    print(highlighted)

Example 3: Entity Statistics

import json
from collections import Counter

with open('results.json') as f:
    data = json.load(f)

# Count entity types across all results
entity_type_counts = Counter()
for result in data['results']:
    for entity_type, entities in result['recognized_entities'].items():
        entity_type_counts[entity_type] += len(entities)

print("Entity type distribution:")
for entity_type, count in entity_type_counts.most_common():
    print(f"  {entity_type}: {count}")

Files Updated

  1. palefire-cli.py - Export function updated
  2. example_export.json - Updated with new format
  3. CLI_GUIDE.md - Documentation updated
  4. EXPORT_FEATURE.md - Examples updated
  5. EXPORT_CHANGES.md - This file (new)

Testing

All changes verified:

  • ✅ Code compiles without errors
  • ✅ JSON format is valid
  • ✅ Documentation updated
  • ✅ Example file updated

See Also

Export Format v2.0 - Smaller, Faster, Better! 🚀