text-processing

The Text-Processing server provides a suite of tools designed to analyze and process text data with ease and accuracy. This server is ideal for developers and data scientists looking to integrate advanced text-processing capabilities into their applications. It offers features such as sentiment analysis, stemming and lemmatization, part-of-speech tagging and chunking, and phrase extraction and named entity recognition. The server is designed to handle large volumes of text efficiently while providing accurate and meaningful insights.

Features

• Sentiment Analysis: Evaluate the sentiment of English text to determine if it conveys a positive, negative, or neutral emotion.
• Stemming and Lemmatization: Process text to identify the base or root form of words, aiding in text normalization and analysis.
• Part-of-Speech Tagging and Chunking: Identify and tag parts of speech in text, extract phrase chunks, and recognize named entities to understand the grammatical structure.
• Phrase Extraction and Named Entity Recognition: Extract meaningful phrases and identify named entities such as people, organizations, and locations within the text.

MCP Tools

• Sentiment Tool: Analyze the sentiment of English text.
• Stem Tool: Stem or lemmatize each word in the given text.
• Tag Tool: Perform part-of-speech tagging, phrase chunking, and named entity recognition on text.
• Phrases Tool: Extract phrase chunks and named entities from text.

Usage with Different Platforms

python

python
import requests

url = 'http://text-processing-server/api'
text = 'Your text here'

# Sentiment Analysis
response = requests.post(f'{url}/sentiment', data={'text': text})
print(response.json())

# Stemming
response = requests.post(f'{url}/stem', data={'text': text})
print(response.json())

# Part-of-Speech Tagging
response = requests.post(f'{url}/tag', data={'text': text})
print(response.json())

# Phrase Extraction
response = requests.post(f'{url}/phrases', data={'text': text})
print(response.json())