RL3 Information Extraction Engine: Information extraction, NER & NLP engine

RL3 Pattern Matching is a rule-based information extraction, named-entity recognition and categorization engine. RL3 is also a programming language intended to simplify implementation, use and support of large libraries of rules and patterns in computational linguistics projects.

Setapp — Grow, and monetize your app with unified AI gateway

Grow, and monetize your app with unified AI gateway

Example on extracting email addresses (anti-scraping protected) from text https://rl3.zorallabs.com/wiki/E...

Simple named entity recognition example https://rl3.zorallabs.com/wiki/N...

In case if you are looking for a reliable solution for entity extraction, then the RL3 engine should be in your shortlist for sure (BTW, is free for non-commercial use!). It is actually based on regex but allows named patterns, modules, templates, and kind of classes. Should you be OK doing some coding and understand NER & NLP basics, lots of helpful staff await you under the hood. For example, some ready-to-use pattern libraries, possibility to reuse patterns by adding them into a custom library, compatibility with third-party dictionaries of enormous size (in the form of text files).

Also, I have had an opportunity to play with an RL3-based web scrapping service which crawls corporate websites (~25 million) and extracts key information such as people, contacts, etc. It is fast, and RL3 patterns work very precisely.

Pros:

A human-friendly regex; an out-of-box & ready-to-use pattern library; three (for now) APIs including Python.

Cons:

Lack of manuals and examples; only Linux-compatible; no UI or web version for non-technical users.