compromise

Compromise: A Modest Natural Language Processing Tool

Overview

Compromise is a natural language processing (NLP) library designed to efficiently and effectively convert text into data. Developed by Spencer Kelly and other contributors, Compromise aims to provide users with straightforward methods to analyze and manipulate textual data. Its focus is on making sensible decisions with text rather than overly complex computations, ensuring a balance between performance and usability.

Features

1. Easy Installation and Setup

   • To start using Compromise, users simply need to run npm install compromise. It can be integrated into modern web applications effortlessly.

2. Basic Text Manipulation

   • Compromise allows users to transform text easily. For instance, it can change verbs into their past tense or convert singular nouns into plurals. This capability makes it ideal for applications requiring dynamic text modification.

   import nlp from 'compromise'
   let doc = nlp('she sells seashells by the seashore.')
   doc.verbs().toPastTense()
   console.log(doc.text()) 
   // Output: 'she sold seashells by the seashore.'
   

3. Pattern Matching and Custom Queries

   • Users can search for specific patterns within text, like detecting verbs or particular sequences, and perform operations based on these patterns.

   if (doc.has('simon says #Verb')) {
     return true
   }
   

4. Data Extraction and Conversion

   • Beyond parsing, Compromise excels in extracting meaningful data from text. Users can leverage JSON outputs to integrate NLP findings into other data pipelines seamlessly.

   import plg from 'compromise-speech'
   nlp.extend(plg)
   
   let doc = nlp('Milwaukee has had many visitors.')
   doc.compute('syllables')
   console.log(doc.places().json())
   

5. Built-in Tools and Functions

   • With utilities to manage contractions and numbers, Compromise simplifies text handling, making it a robust choice for tasks needing clean data transformation.

   let doc = nlp("we're not gonna take it..")
   doc.contractions().expand()
   console.log(doc.text())
   // Output: 'we are not going to take it..'
   

6. Multi-Language Support

   • While primarily focused on English, Compromise extends its functionalities to French, German, Italian, and Spanish, making it versatile for multilingual applications.

Performance and Usability

Compromise is built to be lightweight, with a typical size of around 250kb when minified. This makes it quick enough for real-time applications, such as processing data on keypresses. It also integrates a concise lexicon of approximately 14,000 words to facilitate various NLP tasks efficiently.

API Structure

Compromise is organized into three main modules for targeted functionality:

1. Compromise/one

   • A basic tokenizer that parses text into words and sentences, offering plain access to textual data.

   import nlp from 'compromise/one'
   let doc = nlp("Wayne's World, party time")
   console.log(doc.json())
   

2. Compromise/two

   • Focused on part-of-speech tagging, it identifies and categorizes words to provide grammatical context, enhancing user's ability to parse language structures.

3. Compromise/three

   • Offers tools for phrase and sentence operations, enabling deeper insights into textual data, such as extracting number data or transforming currency formats.

Conclusion

With its pragmatic approach to natural language processing, Compromise stands out as a reliable tool for anyone looking to perform text analysis or conversion. Its blend of simplicity and functionality makes it an excellent choice for developers needing a nimble solution to integrate NLP into their projects.