Text Analysis

Text Processing API

Advanced Natural Language Processing and text analytics.

A powerful API for advanced text processing, offering sentiment analysis, lemmatization, POS tagging, phrase chunking, and named entity recognition (NER) for intelligent automation.

example.py

import requests

# Perform NLP Analysis on Raw Text

def process_nlp(text):

url = "https://text-processing-api.p.rapidapi.com/process"

payload = { "text": text, "tasks": ["sentiment", "ner", "lemma"] }

headers = { "X-RapidAPI-Key": "YOUR_KEY" }

response = requests.post(url, json=payload, headers=headers)

return response.json()

62ms

Latency

96.8%

Accuracy

8+ NLP

Tasks

/ Features

Everything you need, nothing you don't

Sentiment Analysis

Identify emotional polarity and subjectivity scores for user-generated content

Word Lemmatisation

Accurately reduce words to their base linguistic forms for better indexing

POS & Chunking

Deep phrase analysis and parts-of-speech tagging with high-accuracy models

Entity Recognition (NER)

Extract organisations, locations, and names for knowledge base construction

/ Deeper meaning extraction

Advanced NLP Intelligence

Go beyond simple keywords. Our API implements industrial-strength Named Entity Recognition (NER) and Named Entity Linking, allowing you to automatically categorise and relate names, places, and brands found within unstructured text data.

/ Fueling machine learning pipelines

Production-Grade Preprocessing

Ideal for automated categorization and ML feature engineering. Leverage precision lemmatization and POS tagging to normalise text for search engines, sentiment monitoring dashboards, or as a preliminary step for custom LLM fine-tuning.

/ Built with

Python FastAPI SpaCy NLTK

Ready to try Text Processing API?

A powerful API for advanced text processing, offering sentiment analysis, lemmatization, POS tagging, phrase chunking, and named entity recognition (NER) for intelligent automation.

/ Product ecosystem