NumaHub is the future of Artificial Intelligence. Our greyware has been at it, solving a series of problems of the real world using AI - education and retail to start with. With a long history of delivering AI projects to other customers, our team has now embarked on a journey to build AI products under the 'NumaHub' banner, and reaching to customers and enterprises directly. It is our own story, young, vibrant and exciting - we do what we love - using NLP and AI and Machine Learning. Our plans are to roll out a series of creative positive disruptions in education and retail, that our users will love - as we work to enhance their experience.

nounshoun reflects what we are good at - Artificial Intelligence and Grammar. nounshoun is the worlds first "Do it Yourself" Grammer App that uses Artificial Intelligence to help anyone learning English identify the Parts of Speech (Nouns, Verbs, Prepositions etc.,) from any sentence.

Why do it yourself? We believe in learning by trying - and when you are trying things, you have a ready-reckoner with you, wherever you are. nounshoun is your anywhere, anytime companion to learn Parts of Speech.

We would like to take this opportunity to cite the excellent work by the following:

  • Manning, Christopher D., Surdeanu, Mihai, Bauer, John, Finkel, Jenny, Bethard, Steven J., and McClosky, David. 2014. The Stanford CoreNLP Natural Language Processing Toolkit. In Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55-60. View Paper
  • Angel X. Chang and Christopher D. Manning. 2014. TokensRegex: Defining cascaded regular expressions over tokens. Stanford University Technical Report, 2014 View Paper.
  • Marie-Catherine de Marneffe, Bill MacCartney and Christopher D. Manning. 2006. Generating Typed Dependency Parses from Phrase Structure Parses View Paper
  • Kristina Toutanova and Christopher D. Manning. 2000. Enriching the Knowledge Sources Used in a Maximum Entropy Part-of-Speech Tagger. In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-2000) View Paper
  • Kristina Toutanova, Dan Klein, Christopher Manning, and Yoram Singer. 2003. Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. In Proceedings of HLT-NAACL 2003, pp. 252-259. View Paper
  • Jenny Rose Finkel, Trond Grenager, and Christopher Manning. 2005. Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling. Proceedings of the 43nd Annual Meeting of the Association for Computational Linguistics (ACL 2005) View Paper
  • Christopher Manning and Dan Klein. 2003. Optimization, Maxent Models, and Conditional Estimation without Magic. Tutorial at HLT-NAACL 2003 and ACL 2003 View Paper
  • Angel X. Chang and Christopher D. Manning. 2012. SUTIME: A Library for Recognizing and Normalizing Time Expressions. 8th International Conference on Language Resources and Evaluation (LREC 2012). View Paper
  • Princeton University "About WordNet." WordNet. Princeton University. 2010. View
  • NumaHub Users FrameNet Data Release 1.5 by http://framenet.icsi.berkeley.edu licensed under a Creative Commons Attribution 3.0 Unported License  View

  • VerbNet by University of Colorado View
  • PropBank by University of Colorado View