{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Multi-Source Data Integration\n",
        "\n",
        "## Overview\n",
        "\n",
        "This notebook demonstrates advanced multi-source data integration using multiple ingestion types, entity resolution, conflict detection, and provenance tracking.\n",
        "\n",
        "### Learning Objectives\n",
        "\n",
        "- Ingest data from multiple sources (files, web, databases, streams, feeds)\n",
        "- Resolve entities across sources using EntityResolver\n",
        "- Detect conflicts using ConflictDetector\n",
        "- Track provenance using ProvenanceTracker\n",
        "- Integrate data into a unified knowledge graph\n",
        "\n",
        "---\n",
        "\n",
        "## Workflow: Multi-Source Ingestion → Entity Resolution → Conflict Detection → Provenance Tracking → Unified KG\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from semantica.ingest import FileIngestor, WebIngestor, DBIngestor, StreamIngestor, FeedIngestor\n",
        "from semantica.parse import DocumentParser, StructuredDataParser\n",
        "from semantica.kg import GraphBuilder, EntityResolver, ConflictDetector, ProvenanceTracker\n",
        "import tempfile\n",
        "import os\n",
        "import json\n",
        "\n",
        "file_ingestor = FileIngestor()\n",
        "web_ingestor = WebIngestor()\n",
        "db_ingestor = DBIngestor()\n",
        "stream_ingestor = StreamIngestor()\n",
        "feed_ingestor = FeedIngestor()\n",
        "\n",
        "temp_dir = tempfile.mkdtemp()\n",
        "\n",
        "file1 = os.path.join(temp_dir, \"source1.txt\")\n",
        "with open(file1, 'w') as f:\n",
        "    f.write(\"Apple Inc. is a technology company. Tim Cook is the CEO.\")\n",
        "\n",
        "file_objects = file_ingestor.ingest_file(file1, read_content=True)\n",
        "\n",
        "print(f\"Ingested {len([file_objects]) if file_objects else 0} files\")\n",
        "print(f\"Multi-source ingestion initialized\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 2: Entity Resolution\n",
        "\n",
        "Resolve entities across multiple sources.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "entity_resolver = EntityResolver()\n",
        "\n",
        "entities_from_source1 = [\n",
        "    {\"id\": \"e1\", \"name\": \"Apple Inc.\", \"type\": \"Organization\", \"source\": \"file1\"},\n",
        "    {\"id\": \"e2\", \"name\": \"Tim Cook\", \"type\": \"Person\", \"source\": \"file1\"}\n",
        "]\n",
        "\n",
        "entities_from_source2 = [\n",
        "    {\"id\": \"e3\", \"name\": \"Apple Incorporated\", \"type\": \"Organization\", \"source\": \"web\"},\n",
        "    {\"id\": \"e4\", \"name\": \"Timothy Cook\", \"type\": \"Person\", \"source\": \"web\"}\n",
        "]\n",
        "\n",
        "all_entities = entities_from_source1 + entities_from_source2\n",
        "\n",
        "resolved_entities = entity_resolver.resolve(all_entities)\n",
        "\n",
        "print(f\"Original entities: {len(all_entities)}\")\n",
        "print(f\"Resolved entities: {len(resolved_entities)}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 3: Conflict Detection\n",
        "\n",
        "Detect conflicts between sources.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "conflict_detector = ConflictDetector()\n",
        "\n",
        "conflicts = conflict_detector.detect_value_conflicts(all_entities, \"name\")\n",
        "\n",
        "print(f\"Detected {len(conflicts)} conflicts\")\n",
        "for conflict in conflicts[:3]:\n",
        "    print(f\"  Conflict: {conflict.entity_id} - {conflict.conflict_type}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 4: Provenance Tracking\n",
        "\n",
        "Track data provenance across sources.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "provenance_tracker = ProvenanceTracker()\n",
        "\n",
        "for entity in all_entities:\n",
        "    provenance_tracker.track_entity(entity.get(\"id\"), entity.get(\"source\"), entity)\n",
        "\n",
        "relationships = [\n",
        "    {\"source\": \"e2\", \"target\": \"e1\", \"type\": \"CEO_of\", \"source\": \"file1\"}\n",
        "]\n",
        "\n",
        "for rel in relationships:\n",
        "    provenance_tracker.track_relationship(rel.get(\"source\"), rel.get(\"target\"), rel.get(\"source\"), rel)\n",
        "\n",
        "print(f\"Tracked provenance for {len(all_entities)} entities and {len(relationships)} relationships\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 5: Build Unified Knowledge Graph\n",
        "\n",
        "Build a unified knowledge graph from integrated sources.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "builder = GraphBuilder()\n",
        "\n",
        "unified_kg = builder.build(resolved_entities, relationships)\n",
        "\n",
        "print(f\"Built unified knowledge graph\")\n",
        "print(f\"  Entities: {len(unified_kg.get('entities', []))}\")\n",
        "print(f\"  Relationships: {len(unified_kg.get('relationships', []))}\")\n",
        "print(f\"  Sources integrated: {len(set(e.get('source', '') for e in resolved_entities))}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Summary\n",
        "\n",
        "You've learned advanced multi-source data integration:\n",
        "\n",
        "- **Multiple Ingestion Types**: FileIngestor, WebIngestor, DBIngestor, StreamIngestor, FeedIngestor\n",
        "- **EntityResolver**: Resolve entities across sources\n",
        "- **ConflictDetector**: Detect conflicts between sources\n",
        "- **ProvenanceTracker**: Track data provenance\n",
        "- **Unified Knowledge Graph**: Build integrated graph from multiple sources\n"
      ]
    }
  ],
  "metadata": {
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}