NLP Tagging Data Function for Spotfire® 1.0.0

Overview

This script performs both NER tagging and POS tagging. Named entity recognition (NER) extracts pre-defined entities from text that are often indicative of important information. These include names of people, places, locations, etc. Given inputs, the words in the selected text column are tagged by a Named Entity Recognizer. A group of words can be associated with multiple tags as well as the corresponding text it comes from and the id of that text. Part-of-speech tagging is the process of marking a word from text with a part of speech (Noun, Adjective, etc.) based on its definition and context. Given inputs, the words in the selected text column are tagged by a Part-of-Speech Tagger. A single word is associated with a single POS tag as well as the corresponding text it comes from and the id of that text. Written in Python. Requires packages spacy, spacytextblob, time.

Installing the data function

Follow the online guide available here to register a data function in Spotfire

Configuring the data function

Each data function may require inputs from the Spotfire analysis and will return outputs to the Spotfire analysis. For each data function, these need to be configured once the data function is registered. To learn about how to configure data functions in Spotfire please view this video:

For more information on Spotfire visit the Spotfire training page.

Data function library

There exists a large number of data functions covering various features. Feel free to review what is available on the Data Function Library.