{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Temporal Knowledge Graphs\n",
        "\n",
        "## Overview\n",
        "\n",
        "This notebook demonstrates advanced temporal knowledge graph capabilities using TemporalGraphQuery, TemporalPatternDetector, TemporalVersionManager, and TemporalVisualizer.\n",
        "\n",
        "### Learning Objectives\n",
        "\n",
        "- Use TemporalGraphQuery for time-aware queries\n",
        "- Use TemporalPatternDetector to detect temporal patterns\n",
        "- Use TemporalVersionManager for temporal versioning and snapshots\n",
        "- Use TemporalVisualizer to visualize temporal data\n",
        "\n",
        "---\n",
        "\n",
        "## Workflow: Build Temporal KG → Time-Aware Queries → Pattern Detection → Version Management → Visualization\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from semantica.kg import GraphBuilder, TemporalGraphQuery, TemporalPatternDetector, TemporalVersionManager\n",
        "from semantica.visualization import TemporalVisualizer\n",
        "from datetime import datetime\n",
        "\n",
        "builder = GraphBuilder()\n",
        "\n",
        "entities = [\n",
        "    {\"id\": \"e1\", \"type\": \"Organization\", \"name\": \"Apple Inc.\", \"properties\": {\"founded\": \"1976\"}},\n",
        "    {\"id\": \"e2\", \"type\": \"Person\", \"name\": \"Steve Jobs\", \"properties\": {\"born\": \"1955\"}}\n",
        "]\n",
        "\n",
        "relationships = [\n",
        "    {\"source\": \"e2\", \"target\": \"e1\", \"type\": \"founded\", \"properties\": {\"timestamp\": \"1976-04-01\"}}\n",
        "]\n",
        "\n",
        "temporal_kg = builder.build(entities, relationships)\n",
        "\n",
        "print(f\"Built temporal knowledge graph with {len(entities)} entities\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 2: Time-Aware Queries\n",
        "\n",
        "Query the graph at specific time points.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "temporal_query = TemporalGraphQuery()\n",
        "\n",
        "query_result = temporal_query.query_time_range(\n",
        "    graph=temporal_kg,\n",
        "    query=\"Find entities founded in 1976\",\n",
        "    start_time=\"1976-01-01\",\n",
        "    end_time=\"1976-12-31\"\n",
        ")\n",
        "\n",
        "print(f\"Time-aware query returned {len(query_result.get('entities', []))} entities\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 3: Temporal Pattern Detection\n",
        "\n",
        "Detect temporal patterns in the graph.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "pattern_detector = TemporalPatternDetector()\n",
        "\n",
        "patterns = pattern_detector.detect_temporal_patterns(\n",
        "    temporal_kg,\n",
        "    pattern_type=\"sequence\",\n",
        "    min_frequency=1\n",
        ")\n",
        "\n",
        "print(f\"Detected {len(patterns)} temporal patterns\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 4: Version Management\n",
        "\n",
        "Manage temporal versions and snapshots.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "version_manager = TemporalVersionManager()\n",
        "\n",
        "snapshot = version_manager.create_snapshot(temporal_kg, timestamp=datetime.now())\n",
        "\n",
        "print(f\"Created temporal snapshot at {snapshot.get('timestamp', 'N/A')}\")\n",
        "print(f\"Snapshot contains {len(snapshot.get('entities', []))} entities\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 5: Temporal Visualization\n",
        "\n",
        "Visualize temporal data.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "temporal_visualizer = TemporalVisualizer()\n",
        "\n",
        "visualization = temporal_visualizer.visualize_timeline(temporal_kg, output=\"interactive\")\n",
        "\n",
        "print(\"Generated temporal visualization\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Summary\n",
        "\n",
        "You've learned advanced temporal knowledge graph capabilities:\n",
        "\n",
        "- **TemporalGraphQuery**: Time-aware graph querying\n",
        "- **TemporalPatternDetector**: Temporal pattern detection\n",
        "- **TemporalVersionManager**: Temporal versioning and snapshots\n",
        "- **TemporalVisualizer**: Temporal data visualization\n"
      ]
    }
  ],
  "metadata": {
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}