The Layar API has several methods for performing analysis and annotation of text using deep learning models. Each type of NLP tool we outline below provides valuable information for language understanding and information extraction tasks.
- Question answering receives a question provided by a user and then inspects the given text and identifies the most probable answer(s) based on the model's understanding of the question and the text it's looking in. Question answering is performed through the
- Named entity recognition inspects the given text for known entities (common and proper nouns) and returns information about those entities. Named entity recognition is performed with the
- Part-of-Speech analysis extracts linguistic information, breaking up the given text into a series of sentences and tokens for various NLP tasks. Part-of-Speech analysis is performed with the
- Summarization analyzes text content and returns a synopsis of the text. Summarization is performed using the __ method.
- Content classification analyzes text content and returns a category for the content. For example, identifying whether text comes from a clinical trial protocol or from an academic publication. Content classification is performed by using the __ method.
Updated about 1 month ago