Demos

Demos and visualizations aren't just eye candy – they're an essential part of explaining and exploring AI technologies, especially during development. A good visualisation lets you understand your model's behaviour and catch obvious problems early. Our demos include visualisations for spaCy's depency trees, entity recognition and similarity models, along with a word-sense explorer trained on Reddit comments.

displaCy Dependency Visualizer

Visualise spaCy's guess at the syntactic structure of a sentence. Arrows point from children to heads, and are labelled by their relation type.

View demo →

displaCy Named Entity Visualizer

Visualise spaCy's guess at the named entities in the document. You can filter the displayed types, to only show the annotations you're interested in.

View demo →

Rule-based Matcher Explorer

Test spaCy's rule-based Matcher by creating token patterns interactively and running them over your text. Explore how spaCy processes your text – and why your pattern matches, or doesn't.

View demo →

sense2vec: Semantic Analysis of the Reddit Hivemind

Our neural network read every comment posted to Reddit in 2015, and built a semantic map using word2vec and spaCy.

View demo →

Sentence Similarity

Select a model, type two sentences and see what result spaCy's similarity method will produce.

View demo →

Prodigy

Whether you're working on entity recognition, intent detection or image classification, Prodigy can help you train and evaluate your models faster.

View demo →