Text Analytics API Reference

A comprehensive collection of text analytics endpoints that include text summarization, classification, named entity relationship (NER) extraction etc.

The new generation of large language models (LLMs) such as GPT3, GPT4, and ChatGPT/GPT 3.5 have revolutionalized the way we analyze text data.

Out base level text classification endpoint includes few dozen topic labels; however if you are interested a more granular text classifier that contains IAB/IPTC + custom taxonomy) that contains over 1900 topics, please email us at info@specrom.com

Our comprehensive text analytics endpoints uses the latest GPT-J and/or GPT3.5/GPT4 models on the back end to analyze all aspects of the news articles.

Text Language Detection

A Specrom News API endpoint for detecting the language of the input text.

Named Entity Extraction

Extract Named Entities from the input text using our API endpoint.

Text Summarization

This endpoint will generate a summary of the entered text. It uses a state of the art LLM based abstractive summarization model.

Text Classification

Input the headline or meta description of a news article and to generate a topic tag using a text classifier.

Classify News Articles Using Smart Labels

A Specrom News API endpoint for labeling common types of articles seen on news websites

Aspect Based Sentiments Analysis

A Specrom News API endpoint for extracting entities from the input text and predicting the sentiments towards each entities.

Document Sentiments Score

A Specrom News API endpoint for predicting the document level sentiments score for the input text

Keyword or Keyphrase Extraction

A Specrom News API endpoint for extracting keywords or keyphrases from the input text.