introduction-to-word-and-text-embeddings.ipynb

introduction-to-word-and-text-embeddings.ipynb

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        "# Text Embeddings: From Word2Vec to Sentence Transformers\n",
        "\n",
        "This notebook provides a brief introduction to text embeddings, demonstrating how embeddings solve the challenging problem of entity resolution and semantic understanding.\n",
        "\n",
        "## Learning Objectives\n",
        "\n",
        "1. **Foundational Concepts**: How words become numbers that capture semantic meaning\n",
        "2. **Historical Evolution**: The progression from Word2Vec to modern transformer-based embeddings\n",
        "4. **Multilingual Capabilities**: Cross-language semantic understanding and search\n",
        "\n",
        "## Real-World Challenge: Yale's Entity Resolution Problem\n",
        "\n",
        "Consider these two Yale catalog records:\n",
        "- **Franz Schubert** (1797-1828): Austrian composer\n",
        "- **Franz August Schubert** (1806-1893): German artist\n",
        "\n",
        "How can AI systems distinguish between these individuals who share the same name? This tutorial shows how text embeddings solve this fundamental challenge in library science, digital humanities, and knowledge management."
      ]
    },
    {
      "cell_type": "markdown",
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      "source": [
        "# Understanding Word2Vec\n",
        "\n",
        "## Step 1: Install Required Libraries\n",
        "\n",
        "We'll use both historical and modern approaches to understand the evolution of text embeddings:\n",
        "\n",
        "- **`staticvectors`**: Access to Google's original Word2Vec vectors for foundational concepts\n",
        "- **`sentence-transformers`**: Modern multilingual embedding models for comparison\n",
        "- **Visualization libraries**: For understanding high-dimensional vector relationships\n",
        "\n",
        "These tools span the entire evolution from Word2Vec (2013) to current state-of-the-art embeddings."
      ]
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          "text": [
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            "Requirement already satisfied: pycparser in /Users/tt434/Dropbox/YUL/2025/msu/tmp/entity_resolver/venv/lib/python3.13/site-packages (from cffi>=1.14->cryptography->authlib<1.3.2,>=1.2.1->weaviate-client) (2.22)\n",
            "\n",
            "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
            "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
            "✅ Environment ready for comprehensive embeddings exploration!\n",
            "📚 We'll explore: Word2Vec → Tokenization → Modern Embeddings → Production Systems\n"
          ]
        }
      ],
      "source": [
        "# Install comprehensive library set for embeddings tutorial\n",
        "!pip install staticvectors sentence-transformers weaviate-client tiktoken matplotlib seaborn scikit-learn pandas numpy plotly\n",
        "\n",
        "# Import foundational libraries\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.metrics.pairwise import cosine_similarity\n",
        "import plotly.express as px\n",
        "import plotly.graph_objects as go\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "# Set up plotting for clear visualizations\n",
        "plt.style.use('seaborn-v0_8')\n",
        "sns.set_palette(\"husl\")\n",
        "\n",
        "print(\"✅ Environment ready for comprehensive embeddings exploration!\")\n",
        "print(\"📚 We'll explore: Word2Vec → Tokenization → Modern Embeddings → Production Systems\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lJP5LX1DWREz"
      },
      "source": [
        "## Step 2: Load the Historical Word2Vec Model\n",
        "\n",
        "We'll start with Google's original Word2Vec vectors, trained on billions of words from Google News. These 300-dimensional vectors were revolutionary in 2013 for capturing semantic relationships through mathematical operations.\n",
        "\n",
        "### Why Start with Word2Vec?\n",
        "\n",
        "Word2Vec introduced the key insight that **semantic relationships can be captured through vector arithmetic**. The famous example \"king - man + woman = queen\" showed that neural networks could learn abstract linguistic relationships from text patterns alone."
      ]
    },
    {
      "cell_type": "code",
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        "execution": {
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      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Loading Google's original Word2Vec model...\n",
            "(This groundbreaking model was trained on ~100 billion words from Google News)\n",
            "✅ Word2Vec model loaded successfully!\n",
            "\n",
            "🔍 How Word2Vec represents 'library':\n",
            "   Vector dimensions: 300\n",
            "   First 10 values: [ 0.05115361 -0.00022628  0.01177211  0.09214425  0.06097781 -0.00535673\n",
            "  0.00431926  0.06673683  0.00527204 -0.01939433]\n",
            "   Vector magnitude: 1.000\n",
            "\n",
            "💡 Each word becomes a point in 300-dimensional space\n",
            "   Words with similar meanings cluster together\n"
          ]
        }
      ],
      "source": [
        "# Load the original Word2Vec model\n",
        "from staticvectors import StaticVectors\n",
        "\n",
        "print(\"Loading Google's original Word2Vec model...\")\n",
        "print(\"(This groundbreaking model was trained on ~100 billion words from Google News)\")\n",
        "\n",
        "word2vec_model = StaticVectors(\"neuml/word2vec\")\n",
        "print(\"✅ Word2Vec model loaded successfully!\")\n",
        "\n",
        "# Test the model with a simple example\n",
        "test_word = \"library\"\n",
        "vector = word2vec_model.embeddings([test_word])[0]\n",
        "\n",
        "print(f\"\\n🔍 How Word2Vec represents '{test_word}':\")\n",
        "print(f\"   Vector dimensions: {len(vector)}\")\n",
        "print(f\"   First 10 values: {vector[:10]}\")\n",
        "print(f\"   Vector magnitude: {np.linalg.norm(vector):.3f}\")\n",
        "\n",
        "print(\"\\n💡 Each word becomes a point in 300-dimensional space\")\n",
        "print(\"   Words with similar meanings cluster together\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VmDJwTIoWRE0"
      },
      "source": [
        "## Step 3: Understanding Semantic Similarity\n",
        "\n",
        "Let's explore how Word2Vec captures relationships between library-related terms. This will show how semantic similarity emerges from the mathematical structure of vector space."
      ]
    },
    {
      "cell_type": "code",
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          "iopub.status.busy": "2025-07-02T12:39:00.297986Z",
          "iopub.status.idle": "2025-07-02T12:39:00.479311Z",
          "shell.execute_reply": "2025-07-02T12:39:00.478556Z",
          "shell.execute_reply.started": "2025-07-02T12:39:00.298370Z"
        },
        "id": "k7BlN9A6WRE0",
        "outputId": "55b67c70-18cc-46a2-ab76-f6c122f99564"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "📚 Analyzing semantic relationships in library terminology\n",
            "Terms: ['library', 'catalog', 'book', 'manuscript', 'archive', 'collection', 'metadata', 'bibliography', 'librarian', 'repository']\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x800 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "🔍 Key observations:\n",
            "   • Semantically related terms show higher similarity scores\n",
            "   • 'book' and 'manuscript' are closely related\n",
            "   • 'librarian' connects to institutional terms like 'library'\n",
            "   • This emerges from how these words appear in similar contexts\n"
          ]
        }
      ],
      "source": [
        "# Explore semantic relationships in library domain\n",
        "library_terms = [\"library\", \"catalog\", \"book\", \"manuscript\", \"archive\",\n",
        "                 \"collection\", \"metadata\", \"bibliography\", \"librarian\", \"repository\"]\n",
        "\n",
        "print(\"📚 Analyzing semantic relationships in library terminology\")\n",
        "print(\"Terms:\", library_terms)\n",
        "\n",
        "# Get vectors for all terms\n",
        "vectors = word2vec_model.embeddings(library_terms)\n",
        "\n",
        "# Calculate similarity matrix using cosine similarity\n",
        "similarity_matrix = cosine_similarity(vectors)\n",
        "\n",
        "# Create visualization\n",
        "plt.figure(figsize=(10, 8))\n",
        "sns.heatmap(similarity_matrix,\n",
        "            xticklabels=library_terms,\n",
        "            yticklabels=library_terms,\n",
        "            annot=True,\n",
        "            cmap='RdYlBu_r',\n",
        "            center=0.5,\n",
        "            fmt='.3f')\n",
        "plt.title('Word2Vec Semantic Similarity: Library Domain Terms', fontsize=14, pad=20)\n",
        "plt.xlabel('Terms', fontsize=12)\n",
        "plt.ylabel('Terms', fontsize=12)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "print(\"\\n🔍 Key observations:\")\n",
        "print(\"   • Semantically related terms show higher similarity scores\")\n",
        "print(\"   • 'book' and 'manuscript' are closely related\")\n",
        "print(\"   • 'librarian' connects to institutional terms like 'library'\")\n",
        "print(\"   • This emerges from how these words appear in similar contexts\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aapGWDNkWRE0"
      },
      "source": [
        "## Step 4: The Famous King-Queen Analogy\n",
        "\n",
        "This demonstration shows Word2Vec's most famous capability: capturing analogical relationships through vector arithmetic. The model learns that the relationship between \"king\" and \"queen\" is similar to the relationship between \"man\" and \"woman.\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-07-02T12:39:16.644096Z",
          "iopub.status.busy": "2025-07-02T12:39:16.643793Z",
          "iopub.status.idle": "2025-07-02T12:39:16.660315Z",
          "shell.execute_reply": "2025-07-02T12:39:16.659549Z",
          "shell.execute_reply.started": "2025-07-02T12:39:16.644075Z"
        },
        "id": "LnJOI5fTWRE0",
        "outputId": "6c14c647-903e-4c49-9f2d-c66e9314e73d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "🔮 The Classic Word2Vec Analogy Test\n",
            "========================================\n",
            "Question: king - man + woman = ?\n",
            "(In other words: king is to man as ??? is to woman)\n",
            "\n",
            "🎯 Top 5 candidates:\n",
            "   1. queen        (similarity: 0.712)\n",
            "   2. princess     (similarity: 0.590)\n",
            "   3. empress      (similarity: 0.489)\n",
            "   4. duchess      (similarity: 0.437)\n",
            "   5. lady         (similarity: 0.328)\n",
            "\n",
            "✨ The model learned that 'queen' is the female equivalent of 'king'\n",
            "   This relationship was never explicitly programmed!\n",
            "   It emerged from patterns in how these words are used in text.\n"
          ]
        }
      ],
      "source": [
        "def find_analogy(model, word_a, word_b, word_c, candidates=None):\n",
        "    \"\"\"\n",
        "    Find the word that completes the analogy: word_a is to word_b as word_c is to ?\n",
        "    Uses vector arithmetic: word_b - word_a + word_c\n",
        "    \"\"\"\n",
        "    # Get vectors for our three input words\n",
        "    vec_a = model.embeddings([word_a])[0]\n",
        "    vec_b = model.embeddings([word_b])[0]\n",
        "    vec_c = model.embeddings([word_c])[0]\n",
        "\n",
        "    # Perform vector arithmetic: king - man + woman = ?\n",
        "    target_vector = vec_b - vec_a + vec_c\n",
        "\n",
        "    # Test against candidate words\n",
        "    if candidates is None:\n",
        "        candidates = [\"queen\", \"princess\", \"lady\", \"duchess\", \"empress\",\n",
        "                     \"woman\", \"female\", \"girl\", \"mother\", \"wife\"]\n",
        "\n",
        "    similarities = []\n",
        "    for word in candidates:\n",
        "        if word not in [word_a, word_b, word_c]:  # Exclude input words\n",
        "            try:\n",
        "                word_vec = model.embeddings([word])[0]\n",
        "                similarity = cosine_similarity([target_vector], [word_vec])[0][0]\n",
        "                similarities.append((word, similarity))\n",
        "            except:\n",
        "                continue\n",
        "\n",
        "    # Sort by similarity and return top results\n",
        "    similarities.sort(key=lambda x: x[1], reverse=True)\n",
        "    return similarities[:5]\n",
        "\n",
        "# Test the classic analogy\n",
        "print(\"🔮 The Classic Word2Vec Analogy Test\")\n",
        "print(\"=\" * 40)\n",
        "print(\"Question: king - man + woman = ?\")\n",
        "print(\"(In other words: king is to man as ??? is to woman)\")\n",
        "\n",
        "results = find_analogy(word2vec_model, \"man\", \"king\", \"woman\")\n",
        "\n",
        "print(\"\\n🎯 Top 5 candidates:\")\n",
        "for i, (word, score) in enumerate(results, 1):\n",
        "    print(f\"   {i}. {word:<12} (similarity: {score:.3f})\")\n",
        "\n",
        "print(f\"\\n✨ The model learned that '{results[0][0]}' is the female equivalent of 'king'\")\n",
        "print(\"   This relationship was never explicitly programmed!\")\n",
        "print(\"   It emerged from patterns in how these words are used in text.\")"
      ]
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      "source": [
        "## Step 5: Visualizing Vector Relationships\n",
        "\n",
        "Let's create a 2D visualization to see how these analogical relationships work geometrically in vector space."
      ]
    },
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            "🎨 Visualizing Gender Relationships in 2D Vector Space\n",
            "Words to plot: ['man', 'woman', 'king', 'queen', 'boy', 'girl', 'prince', 'princess']\n"
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"
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "🎯 Notice the parallel arrows (green)!\n",
            "   The vector from 'king' to 'queen' is parallel to 'man' to 'woman'\n",
            "   This geometric relationship enables analogical reasoning\n"
          ]
        }
      ],
      "source": [
        "# Visualize the analogy in 2D space\n",
        "analogy_words = [\"man\", \"woman\", \"king\", \"queen\", \"boy\", \"girl\", \"prince\", \"princess\"]\n",
        "\n",
        "print(\"🎨 Visualizing Gender Relationships in 2D Vector Space\")\n",
        "print(\"Words to plot:\", analogy_words)\n",
        "\n",
        "# Get vectors and reduce to 2D using PCA\n",
        "analogy_vectors = word2vec_model.embeddings(analogy_words)\n",
        "pca = PCA(n_components=2, random_state=42)\n",
        "vectors_2d = pca.fit_transform(analogy_vectors)\n",
        "\n",
        "# Create interactive plot\n",
        "fig = go.Figure()\n",
        "\n",
        "# Color-code by gender\n",
        "colors = ['red' if word in ['man', 'boy', 'king', 'prince'] else 'blue'\n",
        "          for word in analogy_words]\n",
        "\n",
        "fig.add_trace(go.Scatter(\n",
        "    x=vectors_2d[:, 0],\n",
        "    y=vectors_2d[:, 1],\n",
        "    mode='markers+text',\n",
        "    marker=dict(size=12, color=colors),\n",
        "    text=analogy_words,\n",
        "    textposition=\"top center\",\n",
        "    textfont=dict(size=14),\n",
        "    name='Words'\n",
        "))\n",
        "\n",
        "# Draw arrows to show relationships\n",
        "king_idx = analogy_words.index('king')\n",
        "queen_idx = analogy_words.index('queen')\n",
        "man_idx = analogy_words.index('man')\n",
        "woman_idx = analogy_words.index('woman')\n",
        "\n",
        "# King -> Queen arrow\n",
        "fig.add_annotation(\n",
        "    x=vectors_2d[queen_idx, 0], y=vectors_2d[queen_idx, 1],\n",
        "    ax=vectors_2d[king_idx, 0], ay=vectors_2d[king_idx, 1],\n",
        "    xref=\"x\", yref=\"y\", axref=\"x\", ayref=\"y\",\n",
        "    arrowhead=2, arrowsize=1, arrowwidth=3, arrowcolor=\"green\"\n",
        ")\n",
        "\n",
        "# Man -> Woman arrow\n",
        "fig.add_annotation(\n",
        "    x=vectors_2d[woman_idx, 0], y=vectors_2d[woman_idx, 1],\n",
        "    ax=vectors_2d[man_idx, 0], ay=vectors_2d[man_idx, 1],\n",
        "    xref=\"x\", yref=\"y\", axref=\"x\", ayref=\"y\",\n",
        "    arrowhead=2, arrowsize=1, arrowwidth=3, arrowcolor=\"green\"\n",
        ")\n",
        "\n",
        "fig.update_layout(\n",
        "    title=\"Word2Vec Analogy: Gender Relationships in 2D Space\",\n",
        "    xaxis_title=\"First Principal Component\",\n",
        "    yaxis_title=\"Second Principal Component\",\n",
        "    height=600,\n",
        "    showlegend=False\n",
        ")\n",
        "\n",
        "fig.show()\n",
        "\n",
        "print(\"🎯 Notice the parallel arrows (green)!\")\n",
        "print(\"   The vector from 'king' to 'queen' is parallel to 'man' to 'woman'\")\n",
        "print(\"   This geometric relationship enables analogical reasoning\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZOz0YDjXWRE0"
      },
      "source": [
        "## Step 6: Entity Resolution with Franz Schubert\n",
        "\n",
        "Now let's apply Word2Vec to our Yale entity resolution challenge. Can word embeddings help distinguish between two people with the same name but different fields of activity?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-07-02T12:40:23.633393Z",
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          "shell.execute_reply": "2025-07-02T12:40:23.644219Z",
          "shell.execute_reply.started": "2025-07-02T12:40:23.633370Z"
        },
        "id": "dL-qYEaHWRE0",
        "outputId": "4fb89bb1-b23c-4474-a9fb-0b8a69e85d88"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "📚 Franz Schubert Entity Resolution Challenge\n",
            "==================================================\n",
            "\n",
            "COMPOSER:\n",
            "  Name: Schubert, Franz, 1797-1828\n",
            "  Work: Symphony No. 9 in C Major 'The Great'\n",
            "  Context: Austrian composer symphony orchestra classical music romantic\n",
            "\n",
            "ARTIST:\n",
            "  Name: Schubert, Franz August, 1806-1893\n",
            "  Work: Archäologie und Photographie: fünfzig Beispiele zur Geschichte und Methode\n",
            "  Context: German artist archaeology photography illustration visual arts\n",
            "\n",
            "🎯 Contextual Similarity Analysis:\n",
            "   Similarity between contexts: 0.532\n",
            "   ⚠️  Moderately different contexts - likely different people\n",
            "\n",
            "💡 The similarity score of 0.532 suggests these are different individuals\n",
            "   Word2Vec successfully captures the contextual differences!\n"
          ]
        }
      ],
      "source": [
        "# Create sample Yale catalog records for entity resolution\n",
        "schubert_records = {\n",
        "    \"composer\": {\n",
        "        \"identity\": \"Schubert, Franz, 1797-1828\",\n",
        "        \"title\": \"Symphony No. 9 in C Major 'The Great'\",\n",
        "        \"subjects\": \"Symphonies; Classical music; Austrian composers; Romantic period\",\n",
        "        \"provision\": \"Vienna: Universal Edition, 1828\",\n",
        "        \"context\": \"Austrian composer symphony orchestra classical music romantic\"\n",
        "    },\n",
        "    \"artist\": {\n",
        "        \"identity\": \"Schubert, Franz August, 1806-1893\",\n",
        "        \"title\": \"Archäologie und Photographie: fünfzig Beispiele zur Geschichte und Methode\",\n",
        "        \"subjects\": \"Photography in archaeology; Archaeological illustration; German artists\",\n",
        "        \"provision\": \"Mainz: P. von Zabern, 1978\",\n",
        "        \"context\": \"German artist archaeology photography illustration visual arts\"\n",
        "    }\n",
        "}\n",
        "\n",
        "def compute_text_embedding(text, model):\n",
        "    \"\"\"\n",
        "    Compute average word embedding for text.\n",
        "    This is a simple but effective approach for document-level representations.\n",
        "    \"\"\"\n",
        "    words = text.lower().split()\n",
        "    vectors = []\n",
        "\n",
        "    for word in words:\n",
        "        try:\n",
        "            clean_word = word.strip('.,;:!?\"()[]{}').lower()\n",
        "            if clean_word:\n",
        "                vector = model.embeddings([clean_word])[0]\n",
        "                vectors.append(vector)\n",
        "        except:\n",
        "            continue  # Skip words not in vocabulary\n",
        "\n",
        "    if vectors:\n",
        "        return np.mean(vectors, axis=0)\n",
        "    else:\n",
        "        return np.zeros(300)  # Word2Vec has 300 dimensions\n",
        "\n",
        "print(\"📚 Franz Schubert Entity Resolution Challenge\")\n",
        "print(\"=\" * 50)\n",
        "\n",
        "for key, record in schubert_records.items():\n",
        "    print(f\"\\n{key.upper()}:\")\n",
        "    print(f\"  Name: {record['identity']}\")\n",
        "    print(f\"  Work: {record['title']}\")\n",
        "    print(f\"  Context: {record['context']}\")\n",
        "\n",
        "# Compute contextual embeddings\n",
        "composer_embedding = compute_text_embedding(schubert_records[\"composer\"][\"context\"], word2vec_model)\n",
        "artist_embedding = compute_text_embedding(schubert_records[\"artist\"][\"context\"], word2vec_model)\n",
        "\n",
        "# Calculate similarity\n",
        "similarity = cosine_similarity([composer_embedding], [artist_embedding])[0][0]\n",
        "\n",
        "print(f\"\\n🎯 Contextual Similarity Analysis:\")\n",
        "print(f\"   Similarity between contexts: {similarity:.3f}\")\n",
        "\n",
        "if similarity < 0.4:\n",
        "    print(\"   ✅ Very different contexts - clearly different people\")\n",
        "elif similarity < 0.7:\n",
        "    print(\"   ⚠️  Moderately different contexts - likely different people\")\n",
        "else:\n",
        "    print(\"   ❌ Similar contexts - might be the same person\")\n",
        "\n",
        "print(f\"\\n💡 The similarity score of {similarity:.3f} suggests these are different individuals\")\n",
        "print(\"   Word2Vec successfully captures the contextual differences!\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vIAOnEb6WRE1"
      },
      "source": [
        "# Part 3: Modern Multilingual Embeddings\n",
        "\n",
        "## Step 9: Transition to Modern Sentence Transformers\n",
        "\n",
        "Now we'll explore modern embedding models that address Word2Vec's limitations. Sentence Transformers use transformer architecture with sophisticated tokenization to create embeddings that work across languages and capture document-level meaning."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-07-02T12:40:40.757520Z",
          "iopub.status.busy": "2025-07-02T12:40:40.757193Z",
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          "shell.execute_reply": "2025-07-02T12:40:45.513727Z",
          "shell.execute_reply.started": "2025-07-02T12:40:40.757497Z"
        },
        "id": "Tinae8OlWRE1",
        "outputId": "24d4c154-2439-4f4d-c82b-28bca36c899c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Loading modern multilingual sentence transformer...\n",
            "Model: paraphrase-multilingual-MiniLM-L12-v2\n",
            "• Supports 50+ languages\n",
            "• Creates 384-dimensional embeddings\n",
            "• Handles entire sentences/documents\n",
            "✅ Modern model loaded successfully!\n",
            "📏 Embedding dimensions: 384\n",
            "🔤 Max sequence length: 128 tokens\n",
            "\n",
            "🔍 Embedding Comparison:\n",
            "   Text: 'Franz Schubert composed beautiful symphonies in Vienna.'\n",
            "   Word2Vec dimensions: 300\n",
            "   Modern dimensions: 384\n",
            "   Word2Vec sample: [0.00623373 0.02625977 0.02904949 0.02650652 0.00442094]\n",
            "   Modern sample: [ 0.22571996  0.15914145 -0.1786943   0.35999924 -0.061935  ]\n",
            "\n",
            "🎯 Key Differences:\n",
            "   • Word2Vec: Averages individual word vectors\n",
            "   • Modern: Understands entire sentence context\n",
            "   • Word2Vec: English-focused training\n",
            "   • Modern: Multilingual from the ground up\n"
          ]
        }
      ],
      "source": [
        "# Load modern multilingual sentence transformer\n",
        "from sentence_transformers import SentenceTransformer\n",
        "\n",
        "print(\"Loading modern multilingual sentence transformer...\")\n",
        "print(\"Model: paraphrase-multilingual-MiniLM-L12-v2\")\n",
        "print(\"• Supports 50+ languages\")\n",
        "print(\"• Creates 384-dimensional embeddings\")\n",
        "print(\"• Handles entire sentences/documents\")\n",
        "\n",
        "modern_model = SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2')\n",
        "\n",
        "print(\"✅ Modern model loaded successfully!\")\n",
        "print(f\"📏 Embedding dimensions: {modern_model.get_sentence_embedding_dimension()}\")\n",
        "print(f\"🔤 Max sequence length: {modern_model.max_seq_length} tokens\")\n",
        "\n",
        "# Compare with Word2Vec approach\n",
        "test_sentence = \"Franz Schubert composed beautiful symphonies in Vienna.\"\n",
        "\n",
        "# Word2Vec approach: average word vectors\n",
        "word2vec_embedding = compute_text_embedding(test_sentence, word2vec_model)\n",
        "\n",
        "# Modern approach: sentence-level understanding\n",
        "modern_embedding = modern_model.encode([test_sentence])[0]\n",
        "\n",
        "print(f\"\\n🔍 Embedding Comparison:\")\n",
        "print(f\"   Text: '{test_sentence}'\")\n",
        "print(f\"   Word2Vec dimensions: {len(word2vec_embedding)}\")\n",
        "print(f\"   Modern dimensions: {len(modern_embedding)}\")\n",
        "print(f\"   Word2Vec sample: {word2vec_embedding[:5]}\")\n",
        "print(f\"   Modern sample: {modern_embedding[:5]}\")\n",
        "\n",
        "print(f\"\\n🎯 Key Differences:\")\n",
        "print(f\"   • Word2Vec: Averages individual word vectors\")\n",
        "print(f\"   • Modern: Understands entire sentence context\")\n",
        "print(f\"   • Word2Vec: English-focused training\")\n",
        "print(f\"   • Modern: Multilingual from the ground up\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L9khC0wXWRE1"
      },
      "source": [
        "## Step 10: Multilingual Semantic Understanding\n",
        "\n",
        "Let's test the model's ability to understand meaning across different languages using examples from Yale's international collections."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2025-07-02T12:40:58.400000Z",
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          "shell.execute_reply": "2025-07-02T12:40:59.082230Z",
          "shell.execute_reply.started": "2025-07-02T12:40:58.399977Z"
        },
        "id": "man3bsabWRE1",
        "outputId": "f839768f-d561-457f-a234-6fe2a75b77a0"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "🌍 Multilingual Document Analysis\n",
            "Documents to compare:\n",
            "   1. Schubert, Franz. Symphony No. 8 in B minor\n",
            "   2. Schubert, Franz. Symphonie n° 8 en si mineur\n",
            "   3. Schubert, Franz. Sinfonie Nr. 8 in h-Moll\n",
            "   4. Shakespeare, William. Romeo and Juliet\n",
            "   5. Digital libraries and AI technology\n",
            "   6. Bibliotecas digitales y tecnología de IA\n",
            "\n",
            "🎯 Cross-Language Similarity Matrix:\n",
            "                   Schubert (EN)  Schubert (FR)  Schubert (DE)  \\\n",
            "Schubert (EN)              1.000          0.943          0.903   \n",
            "Schubert (FR)              0.943          1.000          0.933   \n",
            "Schubert (DE)              0.903          0.933          1.000   \n",
            "Shakespeare (EN)           0.220          0.268          0.294   \n",
            "Digital Tech (EN)          0.006          0.031          0.019   \n",
            "Digital Tech (ES)          0.029          0.052          0.034   \n",
            "\n",
            "                   Shakespeare (EN)  Digital Tech (EN)  Digital Tech (ES)  \n",
            "Schubert (EN)                 0.220              0.006              0.029  \n",
            "Schubert (FR)                 0.268              0.031              0.052  \n",
            "Schubert (DE)                 0.294              0.019              0.034  \n",
            "Shakespeare (EN)              1.000              0.012              0.035  \n",
            "Digital Tech (EN)             0.012              1.000              0.955  \n",
            "Digital Tech (ES)             0.035              0.955              1.000  \n"
          ]
        },
        {
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",
            "text/plain": [
              "<Figure size 1000x800 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "💡 Key Observations:\n",
            "   • Schubert works show high similarity across languages: 0.943 (EN↔FR)\n",
            "   • Technology topics cluster together: 0.955 (EN↔ES)\n",
            "   • Different topics separate clearly: 0.220 (Schubert↔Shakespeare)\n",
            "   • The model understands meaning independent of language!\n"
          ]
        }
      ],
      "source": [
        "# Test cross-language understanding with international catalog examples\n",
        "multilingual_documents = [\n",
        "    \"Schubert, Franz. Symphony No. 8 in B minor\",  # English\n",
        "    \"Schubert, Franz. Symphonie n° 8 en si mineur\",  # French\n",
        "    \"Schubert, Franz. Sinfonie Nr. 8 in h-Moll\",  # German\n",
        "    \"Shakespeare, William. Romeo and Juliet\",  # English literature\n",
        "    \"Digital libraries and AI technology\",  # Technology\n",
        "    \"Bibliotecas digitales y tecnología de IA\",  # Spanish technology\n",
        "]\n",
        "\n",
        "print(\"🌍 Multilingual Document Analysis\")\n",
        "print(\"Documents to compare:\")\n",
        "for i, doc in enumerate(multilingual_documents, 1):\n",
        "    print(f\"   {i}. {doc}\")\n",
        "\n",
        "# Generate embeddings using modern model\n",
        "embeddings = modern_model.encode(multilingual_documents)\n",
        "\n",
        "# Calculate similarity matrix\n",
        "similarity_matrix = cosine_similarity(embeddings)\n",
        "\n",
        "# Create labels for display\n",
        "labels = [\n",
        "    \"Schubert (EN)\",\n",
        "    \"Schubert (FR)\",\n",
        "    \"Schubert (DE)\",\n",
        "    \"Shakespeare (EN)\",\n",
        "    \"Digital Tech (EN)\",\n",
        "    \"Digital Tech (ES)\"\n",
        "]\n",
        "\n",
        "# Create DataFrame for better visualization\n",
        "similarity_df = pd.DataFrame(similarity_matrix, index=labels, columns=labels)\n",
        "\n",
        "print(f\"\\n🎯 Cross-Language Similarity Matrix:\")\n",
        "print(similarity_df.round(3))\n",
        "\n",
        "# Visualize the relationships\n",
        "plt.figure(figsize=(10, 8))\n",
        "sns.heatmap(similarity_matrix,\n",
        "            xticklabels=labels,\n",
        "            yticklabels=labels,\n",
        "            annot=True,\n",
        "            cmap='coolwarm',\n",
        "            center=0.5,\n",
        "            fmt='.3f')\n",
        "plt.title('Modern Multilingual Embeddings: Cross-Language Semantic Similarity', fontsize=14, pad=20)\n",
        "plt.xlabel('Documents', fontsize=12)\n",
        "plt.ylabel('Documents', fontsize=12)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "print(\"\\n💡 Key Observations:\")\n",
        "print(f\"   • Schubert works show high similarity across languages: {similarity_matrix[0, 1]:.3f} (EN↔FR)\")\n",
        "print(f\"   • Technology topics cluster together: {similarity_matrix[4, 5]:.3f} (EN↔ES)\")\n",
        "print(f\"   • Different topics separate clearly: {similarity_matrix[0, 3]:.3f} (Schubert↔Shakespeare)\")\n",
        "print(\"   • The model understands meaning independent of language!\")"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.13.3"
    },
    "colab": {
      "provenance": [],
      "include_colab_link": true
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}