The Natural Language Understanding Global Initiative (NLUGI) has the goal of creating linguistic knowledge, world knowledge, and digital human readers for all major human languages using the open-source natural language development environment (NLDE) NLP++, VisualText, and the Conceptual Grammar.
Next Revolution in Human Langauge
This effort represents the 5th revolution in human language: the migration of knowledge and the use of that knowledge by computers.
Objectives
- To reintroduce engineered Natural Language Understanding systems back into universities and industry.
- To build the foundation to create trustworthy digital human readers that are equal or better than humans at understanding text for specific tasks.
Philosophy
- Linguistic and world knowledge must be given to computers since symbol and word meaning is arbitrary and cannot be found statistically.
- Intelligent programs must understand text the same way as humans.
- Digital Human Readers must be 100% code and their outputs 100% explainable to be trusted.
- A common computing language like NLP++ is essential for the success of the NLU Global Initiative.
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Latest Posts
ACL 2024 in Bangkok Thailand: Revelations of Old and New
I have been in computational linguistics for more than 40 years, and this is the first time I have been to the most important conference in our field: the annual Association of Computational Linguistics (ACL) Conference. As part of the registration process, I became a member for the first time […]
Global Dictionary Initiative
Part of the Natural Language Understanding Global Initiative is the Global Dictionary Initiative. The idea is to product NLP++ dictionary files for all the major languages of the world. VisualText and NLP++ are being used to parse Wiktionary pages as well as other digital resources in order to create NLP++ […]
RV University and NLU Global Initiative Announce Cooperation
The Computer Science & Engineering Department at RV University in India has come to a long-term formal agreement with the Natural Language Understanding Global Initiative to work on rule-based NLP. Lead by Dr. G Shobha, dean of the School of Computer Science and Engineering, and Dr. Merin Thomas, the school […]
Dr. Merin Thomas
Dr Merin Thomas, currently working as Associate Professor in the School of Computer Science and Engineering, R V University. She has her Specialization in Machine Learning and Artificial Intelligence. Her area of research is in Natural Language Processing. She is a Passionate Teacher and has several research articles to her […]
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Building an NLP++ Brazilian Address Cleaner for HPCC Systems
Live Talk Open to the Public Watch the live presentation of this NLP++ analyzer for Portuguese addresses during the 2024 HPCC Systems Community Summit. It took place on Wednesday, October 8, at 9:00 am EST USA online. It was free to register and attend. Using the NLP++ Plugin for HPCC […]
Regex for NLP
Regex is ubiquitous in the programming world because of its usefulness as a rule-based text parsing language. Programmers find comfort in the idea of writing explicit, modifiable rules in order to parse text. This is in contrast with black-box statistical models, which cannot be modified when things go wrong – […]
NLP++ and LLM
Trustworthy NLP systems must be rule and knowledge based given all statistical systems like large language models, machine learning, and neural networks are not. With the advent of large language models that can be queried about common knowledge, it is natural to use them to generate linguistic and world knowledge […]
Guilherme Santos da Silva
Guilherme Santos da Silva has a degree in Computer Engineering from the Federal Technological University of Paraná, Brazil and is currently an employee of LexisNexis Risk Brazil. He discovered HPCC Systems in 2021 when he joined LexisNexis as an intern and participated in the 2021 HPCC Systems Poster Contest with […]
Scalable Analysis of English Dictionary Files on HPCC Systems Big Data Platform
Congratulations to Jayanth C on presenting his paper on Scalable Analysis of English Dictionary Files on HPCC Systems Big Data Platform at a conference in Japan. Read more about it on LinkedIn. Here are links to the paper online:
Online Dictionary Creation Tool
Coming 2024 This is an exciting project that is currently being implemented. Expected first version release data in 2024. Description The dictionary tool is a web-based tool that will allow for quick creation of dictionaries in any language. Given there are few linguistic dictionaries available online for even major languages […]
Python Package for NLP++
The first version of our NLPPlus python package is ready to use. We are still waiting on approval of the package on the python package website, but it is available as a download from our GitHub. https://github.com/VisualText/py-package-nlpengine The NLPPlus python package for NLP++ allows Python programmers to call NLP++ analyzers […]
Portuguese Dictionary
The first steps in creating a portuguese dictionary has been started and can be found in the GitHub repository: http://github.com/VisualText/dict-pt-br. This was started by NLP++ co-author David de Hilster given he is fluent in Portuguese and that no digital dictionary for portuguese is available. Video Sessions This is a video […]
English Dictionary
This project involves parsing the Wiktionary pages for English into the most comprehensive digital dictionary ever created. The first two stages of this project have been done via grants to RV College of Engineering from LexisNexis Risk’s HPCC Systems group. In Progress This project is still in progress. Project Description […]
Dr. Jyoti Shetty
Dr. Jyoti Shetty is an Assistant Professor in the Computer Science and Engineering Department at the RV College of Engineering. In collaboration with students, she has executed several projects on HPCC Systems, including implementing a distributed DBSCAN, providing evaluation metrics for a clustering algorithm, and IoT plugin for HPCC Systems, an OpenCV […]