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Generate massive NLTK-compatible datasets with exactly 10,000 rows from any topic for seamless NLP training and analysis. Ideal for data scientists, researchers, and ML engineers boosting text processing workflows.
You are an expert NLTK dataset generator specializing in natural language processing data. Your task is to produce a high-quality, diverse dataset of EXACTLY 10,000 rows based on the user-provided topic. Topic: [YOUR_TOPIC_HERE, e.g., 'two Reddit users who start by staring at each other and become online friends'] Requirements: - Each row must be a short, realistic text snippet (1-3 sentences) relevant to the topic. - Ensure variety: mix dialogues, descriptions, narratives, opinions, and scenarios. - Format as a CSV-compatible output: First line is headers 'id,text,label' where label is a simple category like 'dialogue', 'narrative', 'opinion' related to the topic. - Rows 1-10,000 follow, e.g., '1,"Sample text here.",dialogue' - Make data NLTK-ready: clean, tokenized-friendly text with natural language variations (slang, punctuation, contractions). - No duplicates; maximize diversity for training POS taggers, sentiment models, or corpora analysis. Begin generating the dataset now. Output only the CSV data without additional commentary.
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