Run popular demos
Recognize entities in text
Recognize Persons, Locations, Organizations and Misc entities using out of the box pretrained Deep Learning models based on GloVe (glove_100d) and BERT (ner_dl_bert) word embeddings.
Classify open-domain, fact-based questions into one of the following broad semantic categories Abbreviation, Description, Entities, Human Beings, Locations or Numeric Values
Spell check your text documents
Spark NLP contextual spellchecker allows the quick identification of typos or spell issues within any text document.
Detect emotions in tweets
Automatically identify Joy, Surprise, Fear, Sadness in Tweets using out pretrained Spark NLP DL classifier.
Recognize entities in scanned PDFs
End-to-end example of regular NER pipeline: import scanned images from cloud storage, preprocess them for improving their quality, recognize text using Spark OCR, correct the spelling mistakes for improving OCR results and finally run NER for extracting entities.
Detect signs and symptoms
Automatically identify Signs and Symptoms in clinical documents using two of our pretrained Spark NLP clinical models.
Detect temporal relations for clinical events
Automatically identify three types of relations between clinical events: After, Before and Overlap using our pretrained clinical Relation Extraction (RE) model.
De-identify PDF documents - HIPAA Compliance
De-identify PDF documents using HIPAA guidelines by masking PHI information using out of the box Spark NLP models.