RSK World - Named Entity Recognition Dataset - Project Files Browser | RSK World

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    <!--
    Project: Named Entity Recognition Dataset
    Author: RSK World
    Website: https://rskworld.in
    Email: help@rskworld.in
    Phone: +91 93305 39277
    Description: Main landing page for Named Entity Recognition Dataset with animations
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    <title>Named Entity Recognition Dataset | RSK World</title>
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        /* Features Section */
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        /* Stats Section */
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        /* Technologies Section */
        .technologies {
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        .tech-badge span {
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        /* Use Cases Section */
        .use-cases {
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        .use-cases .container {
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        .use-case-card ul li::before {
            content: '✓';
            position: absolute;
            left: 0;
            color: #667eea;
            font-weight: bold;
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        /* Footer */
        footer {
            background: #2c3e50;
            color: white;
            padding: 50px 20px 20px;
            position: relative;
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        .footer .container {
            max-width: 1200px;
            margin: 0 auto;
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        .footer-content {
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            gap: 40px;
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        .footer-section h3 {
            margin-bottom: 20px;
            color: #4ECDC4;
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        .footer-section ul {
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        .footer-section ul li {
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        .footer-section a {
            color: #ecf0f1;
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            transition: all 0.3s;
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        .footer-section a:hover {
            color: #4ECDC4;
            transform: translateX(5px);
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        .footer-bottom {
            text-align: center;
            padding-top: 30px;
            border-top: 1px solid rgba(255,255,255,0.1);
            opacity: 0.8;
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        .social-links {
            display: flex;
            gap: 15px;
            margin-top: 15px;
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        .social-links a {
            width: 40px;
            height: 40px;
            background: rgba(255,255,255,0.1);
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            justify-content: center;
            transition: all 0.3s;
        }

        .social-links a:hover {
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            box-shadow: 0 5px 15px rgba(78, 205, 196, 0.4);
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        /* Scroll to Top Button */
        .scroll-top {
            position: fixed;
            bottom: 30px;
            right: 30px;
            width: 50px;
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            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            color: white;
            border: none;
            border-radius: 50%;
            cursor: pointer;
            display: none;
            align-items: center;
            justify-content: center;
            font-size: 20px;
            box-shadow: 0 5px 15px rgba(0,0,0,0.3);
            transition: all 0.3s;
            z-index: 999;
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        .scroll-top:hover {
            transform: translateY(-5px) scale(1.1);
            box-shadow: 0 8px 20px rgba(0,0,0,0.4);
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        .scroll-top.visible {
            display: flex;
            animation: bounce 2s infinite;
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        @keyframes bounce {
            0%, 100% { transform: translateY(0); }
            50% { transform: translateY(-10px); }
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        @keyframes fadeInUp {
            from {
                opacity: 0;
                transform: translateY(30px);
            }
            to {
                opacity: 1;
                transform: translateY(0);
            }
        }

        /* Dataset Display Section */
        .dataset-section {
            padding: 100px 20px;
            background: #f8f9fa;
        }

        .dataset-section .container {
            max-width: 1200px;
            margin: 0 auto;
        }

        .dataset-tabs {
            display: flex;
            gap: 10px;
            margin-bottom: 20px;
            border-bottom: 2px solid #ddd;
            justify-content: center;
        }

        .dataset-tab {
            padding: 15px 30px;
            background: #f8f9fa;
            border: none;
            border-bottom: 3px solid transparent;
            cursor: pointer;
            font-weight: 600;
            color: #666;
            transition: all 0.3s;
            border-radius: 8px 8px 0 0;
        }

        .dataset-tab.active {
            color: #667eea;
            border-bottom-color: #667eea;
            background: white;
        }

        .dataset-tab:hover {
            color: #667eea;
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        .dataset-content {
            display: none;
            background: white;
            padding: 30px;
            border-radius: 8px;
            box-shadow: 0 5px 15px rgba(0,0,0,0.1);
        }

        .dataset-content.active {
            display: block;
        }

        .data-search {
            margin-bottom: 20px;
        }

        .data-search input {
            width: 100%;
            padding: 12px 15px;
            border: 2px solid #ddd;
            border-radius: 8px;
            font-size: 16px;
        }

        .data-search input:focus {
            outline: none;
            border-color: #667eea;
        }

        .data-samples {
            max-height: 600px;
            overflow-y: auto;
            padding-right: 10px;
        }

        .data-sample {
            background: #f8f9fa;
            padding: 20px;
            margin-bottom: 15px;
            border-radius: 8px;
            border-left: 4px solid #667eea;
            transition: all 0.3s;
        }

        .data-sample:hover {
            box-shadow: 0 5px 15px rgba(0,0,0,0.1);
            transform: translateX(5px);
        }

        .data-sample-header {
            display: flex;
            justify-content: space-between;
            align-items: center;
            margin-bottom: 10px;
        }

        .data-sample-id {
            font-weight: bold;
            color: #667eea;
            font-size: 1.1em;
        }

        .data-sample-entities {
            display: flex;
            flex-wrap: wrap;
            gap: 5px;
            margin-top: 10px;
        }

        .data-sample-text {
            line-height: 1.8;
            font-size: 16px;
            color: #333;
        }

        .data-stats {
            background: white;
            padding: 20px;
            border-radius: 8px;
            margin-bottom: 20px;
            display: grid;
            grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
            gap: 15px;
        }

        .data-stat-item {
            text-align: center;
            padding: 15px;
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            border-radius: 8px;
            color: white;
        }

        .data-stat-item h4 {
            font-size: 2em;
            color: white;
            margin-bottom: 5px;
        }

        .data-stat-item p {
            color: rgba(255,255,255,0.9);
            font-size: 0.9em;
        }

        .entity {
            padding: 3px 6px;
            border-radius: 4px;
            font-weight: 600;
            margin: 0 2px;
            display: inline-block;
        }

        .entity-PERSON {
            background-color: #FF6B6B;
            color: white;
        }

        .entity-ORG {
            background-color: #4ECDC4;
            color: white;
        }

        .entity-LOC {
            background-color: #45B7D1;
            color: white;
        }

        .entity-DATE {
            background-color: #FFA07A;
            color: white;
        }

        .entity-MONEY {
            background-color: #98D8C8;
            color: #333;
        }

        .entity-PERCENT {
            background-color: #F7DC6F;
            color: #333;
        }

        @media (max-width: 768px) {
            .hero h2 {
                font-size: 2em;
            }
            nav ul {
                flex-direction: column;
                gap: 10px;
            }
            .section-title {
                font-size: 2em;
            }
        }
    </style>
</head>
<body>
    <!-- Header -->
    <header id="header">
        <div class="header-top">
            <div class="container">
                <div>
                    <a href="mailto:help@rskworld.in"><i class="fas fa-envelope"></i> help@rskworld.in</a>
                    <a href="tel:+919330539277"><i class="fas fa-phone"></i> +91 93305 39277</a>
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                        <h1>NER Dataset</h1>
                        <p>Named Entity Recognition</p>
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            <h2>Named Entity Recognition Dataset</h2>
            <p>Comprehensive dataset with labeled entities for information extraction and NLP model training</p>
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                    <span><i class="fas fa-play"></i> Try Demo</span>
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    <!-- Features Section -->
    <section class="features" id="features">
        <div class="container">
            <h2 class="section-title fade-in">Key Features</h2>
            <p class="section-subtitle fade-in">Everything you need for Named Entity Recognition projects</p>
            <div class="features-grid">
                <div class="feature-card fade-in">
                    <div class="feature-icon"><i class="fas fa-tags"></i></div>
                    <h3>Labeled Entities</h3>
                    <p>Pre-labeled entities including persons, organizations, locations, dates, and more for immediate use in your projects.</p>
                </div>
                <div class="feature-card fade-in">
                    <div class="feature-icon"><i class="fas fa-layer-group"></i></div>
                    <h3>Multiple Entity Types</h3>
                    <p>Support for PERSON, ORG, LOC, DATE, MONEY, and PERCENT entity types with comprehensive coverage.</p>
                </div>
                <div class="feature-card fade-in">
                    <div class="feature-icon"><i class="fas fa-code"></i></div>
                    <h3>BIO Tagging Format</h3>
                    <p>Includes BIO (Beginning-Inside-Outside) tagging format ready for sequence labeling models.</p>
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                    <h3>Training & Test Sets</h3>
                    <p>Pre-split training and test datasets for immediate model training and evaluation.</p>
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                    <h3>Ready for NER Models</h3>
                    <p>Compatible with spaCy, NLTK, Transformers, and other popular NLP frameworks.</p>
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                    <h3>Multiple Formats</h3>
                    <p>Available in CSV, JSON, and BIO formats for maximum flexibility and compatibility.</p>
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                    <h3>Batch Processing</h3>
                    <p>Advanced batch processing capabilities with parallel processing support for large datasets.</p>
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                    <h3>Advanced Analytics</h3>
                    <p>Comprehensive statistics and analytics tools for dataset analysis and quality assessment.</p>
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                    <h3>REST API</h3>
                    <p>Built-in Flask API server for programmatic access to dataset and entity extraction.</p>
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                    <h3 class="counter" data-target="50">0</h3>
                    <p>Training Samples</p>
                </div>
                <div class="stat-card fade-in">
                    <h3 class="counter" data-target="30">0</h3>
                    <p>Test Samples</p>
                </div>
                <div class="stat-card fade-in">
                    <h3 class="counter" data-target="6">0</h3>
                    <p>Entity Types</p>
                </div>
                <div class="stat-card fade-in">
                    <h3 class="counter" data-target="5">0</h3>
                    <p>Data Formats</p>
                </div>
            </div>
        </div>
    </section>

    <!-- Chart Section -->
    <section class="chart-section">
        <div class="container">
            <h2 class="section-title fade-in">Entity Distribution</h2>
            <p class="section-subtitle fade-in">Visual representation of entity types in the dataset</p>
            <div class="chart-container fade-in">
                <canvas id="entityChart"></canvas>
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            <p class="section-subtitle fade-in">Real-world applications of Named Entity Recognition</p>
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                <div class="use-case-card slide-in-left">
                    <h4><i class="fas fa-newspaper"></i> Information Extraction</h4>
                    <ul>
                        <li>Extract entities from news articles</li>
                        <li>Identify key information in documents</li>
                        <li>Automated content analysis</li>
                    </ul>
                </div>
                <div class="use-case-card fade-in">
                    <h4><i class="fas fa-search"></i> Search & Discovery</h4>
                    <ul>
                        <li>Enhanced search capabilities</li>
                        <li>Semantic search implementation</li>
                        <li>Content recommendation systems</li>
                    </ul>
                </div>
                <div class="use-case-card slide-in-right">
                    <h4><i class="fas fa-comments"></i> Chatbots & NLP</h4>
                    <ul>
                        <li>Conversational AI systems</li>
                        <li>Intent recognition</li>
                        <li>Context understanding</li>
                    </ul>
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                <div class="use-case-card slide-in-left">
                    <h4><i class="fas fa-shield-alt"></i> Security & Compliance</h4>
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                        <li>Data privacy protection</li>
                        <li>Compliance monitoring</li>
                        <li>Anonymization systems</li>
                    </ul>
                </div>
                <div class="use-case-card fade-in">
                    <h4><i class="fas fa-briefcase"></i> Business Intelligence</h4>
                    <ul>
                        <li>Competitor analysis</li>
                        <li>Market research automation</li>
                        <li>Customer data extraction</li>
                    </ul>
                </div>
                <div class="use-case-card slide-in-right">
                    <h4><i class="fas fa-graduation-cap"></i> Research & Education</h4>
                    <ul>
                        <li>Academic research tools</li>
                        <li>Educational applications</li>
                        <li>NLP model training</li>
                    </ul>
                </div>
            </div>
        </div>
    </section>

    <!-- Technologies Section -->
    <section class="technologies" id="technologies">
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            <h2 class="section-title fade-in">Technologies</h2>
            <p class="section-subtitle fade-in">Compatible with popular NLP frameworks and tools</p>
            <div class="tech-list">
                <div class="tech-badge scale-in"><span>CSV</span></div>
                <div class="tech-badge scale-in"><span>JSON</span></div>
                <div class="tech-badge scale-in"><span>spaCy</span></div>
                <div class="tech-badge scale-in"><span>NLTK</span></div>
                <div class="tech-badge scale-in"><span>Transformers</span></div>
                <div class="tech-badge scale-in"><span>PyTorch</span></div>
                <div class="tech-badge scale-in"><span>TensorFlow</span></div>
                <div class="tech-badge scale-in"><span>scikit-learn</span></div>
                <div class="tech-badge scale-in"><span>Flask</span></div>
                <div class="tech-badge scale-in"><span>Pandas</span></div>
            </div>
        </div>
    </section>

    <!-- Dataset Display Section -->
    <section class="dataset-section" id="dataset">
        <div class="container">
            <h2 class="section-title fade-in">Complete Dataset</h2>
            <p class="section-subtitle fade-in">Browse all training and test samples with labeled entities</p>
            
            <div class="dataset-tabs">
                <button class="dataset-tab active" onclick="showDataset('train', this)">
                    <i class="fas fa-graduation-cap"></i> Training Data (50 samples)
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                    <i class="fas fa-vial"></i> Test Data (30 samples)
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                    <h3>About</h3>
                    <p>Named Entity Recognition Dataset for information extraction and NLP model training. Created by RSK World.</p>
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