Recognize Entities - Spark NLP Demos & Notebooks

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Recognize Entities - Live Demos & Notebooks

Recognize 66 Entities in Text (Few-NERD)
Recognize 66 Entities in Text (Few-NERD)
Detect 66 general entities such as art, newspaper, director, war, airport etc., using pretrained Spark NLP NER model. (...)
Recognize 18 Entities in Text (OntoNotes)
Recognize 18 Entities in Text (OntoNotes)
Recognize over 18 entities such as Countries, People, Organizations, Products, Events, etc. using an out of the box pretrained NerDLApproach trained on the OntoNotes corpus. (...)
Detect Key Phrases (Unsupervised)
Detect Key Phrases (Unsupervised)
Automatically detect key phrases in your text documents using out-of-the-box Spark NLP models. (...)
Find Text in a Document (Rule-Based)
Find Text in a Document (Rule-Based)
Finds a text in document either by keyword or by regex expression. (...)
Recognize entities in text
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. (...)
Detect and normalize dates
Detect and normalize dates
Automatically detect key phrases expressing dates and normalize them with respect to a reference date. (...)
Detect Entities in tweets
Detect Entities in tweets
This demo shows how to extract Named Entities, as PER, ORG or LOC, from tweets. (...)
Recognize Restaurant Terminology
Recognize Restaurant Terminology
This demo shows how to extract restaurant-related terminology from texts. (...)
Recognize Time-related Terminology
Recognize Time-related Terminology
This demo shows how to extract time-related terminology from texts. (...)
Detect traffic information in German
Detect traffic information in German
Automatically extract geographical location, postal codes, and traffic routes in German text using our pretrained Spark NLP model. (...)