Semantic Entity Extractor (TextRank)
Discover which concepts actually dominate your text. This tool runs the TextRank algorithm in your browser — building a word co-occurrence graph, scoring it with PageRank, and surfacing the top entities, key phrases, and their connections.
Tool interface
Results
Top entities (TextRank score)
Co-occurrence network
Key phrases
Introduction
TextRank is an unsupervised keyword-extraction algorithm (the basis of many "automatic keyword" features). Running it locally lets you see your text's true conceptual focus without sending it to a cloud NLP service.
How it works
- Tokenize and remove stopwords.
- Build a co-occurrence graph over a sliding window.
- Run PageRank iterations to score each word.
- Rank entities, derive key phrases, and render the network.
Privacy
All computation is local. No upload, no account, no API key, no cloud NLP.
Limitations
- TextRank is compute-heavy; very long documents are sampled for responsiveness.
- Single-word entities; multi-word detection is heuristic via key phrases.
FAQ
Is this the same as TF-IDF?
No. TF-IDF needs a corpus; TextRank works on a single document using a graph, which is why it runs fully client-side.
Is my text uploaded?
No. Everything runs in your browser.
Related tools
References
- Mihalcea & Tarau (2004) — TextRank: Bringing Order into Texts