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NLP Tutorial Analyzers
Analyzers used in the NLP Video Tutorial 1s.
Video Tutorials Playlist
The video tutorials playlist can be found at http://tutorials.visualtext.org
Tutorial 01: NLP++ Tokenization
NLP++ tokenization is explained: YouTube Video Tutorial 1
Tutorial 02: NLP++ Variables Explained
The five NLP++ variables are explained including N, S, X, G, and L: YouTube Video Tutorial 2
Tutorial 03: NLP++ Recursion
NLP++ allows for recursion in the analyzer sequence: YouTube Video Tutorial 3
Tutorial 04: NLP++ Special Variables
Special variables in NLP++ always have a dollar sign and enclosed in double quotes: YouTube Video Tutorial 4
Tutorial 05: Paragraphs & Sentences
See how to parse text into paragraphs and sentences using Library pass files and some custom code when needed: YouTube Video Tutorial 5
Tutorial 06: Automatic Rule & Path Generation
VisualText has two handy operations that allow for automatically generating rules and paths in pass files.: YouTube Video Tutorial 4
Tutorial 07: NLP++ Regions
This explains NLP++ several major regions for code, functions, and rule matching: YouTube Video Tutorial 7
Tutorial 08 (Part 1): Resolving Pronouns by Building KBs on the Fly
Part one is an overview. NLP++ allows for the building of knowledge bases from text on the fly that can be used to parse the text itself. The analyzer in this tutorial shows how NLP++ can resolve pronouns or what is known in linguistics as anaphora: YouTube Video Tutorial 8-1
Tutorial 08 (Part 2): Resolving Pronouns by Building KBs on the Fly
Part two steps through the analyzer sequence in detail. NLP++ allows for the building of knowledge bases from text on the fly that can be used to parse the text itself. The analyzer in this tutorial shows how NLP++ can resolve pronouns or what is known in linguistics as anaphora: YouTube Video Tutorial 8-2
Tutorial 09: NLP++ Rules Explained
NLP++ has a very powerful rule language which is explained in detailed by one of the architects of NLP++, David de Hilster: YouTube Video Tutorial 9
Tutorial 10: Intelligent Programming with NLP++
** NOTE: There is no NLP++ analyzer with this video.**
David talks about the way to go about programming using NLP++. It's a paradigm shift in programming where you need to think about how humans do a task and not how to write that task in a programming language: YouTube Video Tutorial 10
Tutorial 11: Dictionaries in NLP++
Learn about how to create dictionaries in NLP++: YouTube Video Tutorial 11
Tutorial 12: New DICT files
Tutorial on the new dict files for NLP++ that greatly simplifies and organizes dictionaries. This tutorial uses the full english parser (parse-en-us) found in the example analyzers folder which comes with the VSCode NLP++ Language extension: YouTube Video Tutorial 12
Tutorial 13: VisualText Version 2
This tutorial shows of verion 2 of the NLP Engine and VisualText. The main difference is the KB View with the new dictionary and KBB files and the great tools for building and maintaining NLP analyzers that feed one into another: YouTube Video Tutorial 13
Tutorial 13-a:
This analyzer fetches informational pages from the web on the 50 American states. This is included in one video: YouTube Video Tutorial 13
Tutorial 13-b:
This analyzer analyzes the 50 state webpages and creates dictionaries and a knowledge base. This is included in one video: YouTube Video Tutorial 13
Tutorial 14: Mod Files
Mod files allow for bundling text, NLP++ code (passes), dictionaries, and knowledge base files into one file that can be easily created and loaded into VisualText (the NLP++ langauge extension for VSCode).: YouTube Video Tutorial 14
Tutorial 15: Resolving Ambiguity
This tutorial you will learn about the new mechanisms to help resolve with ambiguity. Ambiguity is when a word in isolation can have more than one meaning. Dealing with ambiguity in NLP++ is a cordinated effort between dictionaries, knowledge bases, and rule matching. YouTube Video Tutorial 14