Next Word Prediction Interactive Tool
Train a small n-gram language model, type a context, predict likely next words, and inspect probability, smoothing, and generation calculations.
Browser-based NLP tools for preprocessing, sentiment, retrieval, question answering, translation, summarisation, speech-to-text, entities, POS tagging, and language generation.
All tools
Train a small n-gram language model, type a context, predict likely next words, and inspect probability, smoothing, and generation calculations.
Paste or upload text and inspect tokenization, stop word removal, stemming, lemmatization, n-grams, entities, POS signals, and text statistics.
Build a mini search engine in the browser: edit documents, enter a query, rank results with TF-IDF and cosine similarity, and inspect the retrieval calculations.
Explore simple language generation with a browser-based n-gram model, inspect next-token probabilities, and generate short continuations from custom text.
Check your text for style, clarity, passive voice, weasel words, and sensitive language — a free, browser-based alternative to Grammarly powered by open NLP tools.
Identify people, places, organisations, dates, and other entity-like signals from text using a browser-based NLP workflow.
Paste text and inspect how a browser-based NLP pipeline highlights noun phrases, verbs, adjectives, and token-level language structure for classroom analysis.
Use your microphone to turn short spoken phrases into text in the browser and inspect live transcription output for teaching speech-to-text workflows.
Paste a passage, ask a question, and see how a transformer reading-comprehension model selects an answer span from the provided context.
Translate short passages between supported languages using a browser transformer model, and learn how encoder-decoder translation works.
Paste a paragraph and see how a transformer summarisation model compresses the main ideas into a shorter summary, with clear metrics.
Type text and see how a transformer model predicts positive, negative, or neutral/uncertain sentiment with confidence scores.