POSTagger
This is a repos for practical of Computational Linguisitics at Oxford. This is a POS tagger, implemented seperately by HMM and ConvNet. This work mainly refers to several works as follows.
Structure
The project structure is as follows
- luaSrc is the src folder for training embeddings and postagger, backended by Neural Network
- src/main/scala is the src folder for training HMM n-gram, namely bigram and trigram model. Furthermore, there are some other utilities used in the project are implemented in scala, such as FilePermutator and CorpusManager.
- doc is the document folder, storing the technical report of the practical.
- res (which is invisible in github repos), is the folder for storing the corpus and the wikipedia xml dump.
- lib (which is invisible in github repos), is the folder for storing the unmanaged libraries.
Build
Download the 0.13.* SBT and clone the repos. Just enter the following command in the cloned folder
sbt compile
The command will build the scala part of project automatically
#Dependencies
This project depends on the following libraries, which are not managed by sbt.
- fbcunn
- BIDMat
- torch 7
- Stanford NLTK
In order to build the whole practical, and also the lua part of it, ensure you install the libraries.
Reference
- Collobert, Ronan, et al. "Natural language processing (almost) from scratch." The Journal of Machine Learning Research 12 (2011): 2493-2537.
- Chen, Stanley F., and Joshua Goodman. "An empirical study of smoothing techniques for language modeling." Proceedings of the 34th annual meeting on Association for Computational Linguistics. Association for Computational Linguistics, 1996.
- Collobert, Ronan, Koray Kavukcuoglu, and Clément Farabet. "Torch7: A matlab-like environment for machine learning." BigLearn, NIPS Workshop. No. EPFL-CONF-192376. 2011.
- Canny, John, and Huasha Zhao. "Bidmach: Large-scale learning with zero memory allocation." BigLearn Workshop, NIPS. 2013.
- Manning, Christopher D., et al. "The Stanford CoreNLP natural language processing toolkit." Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 2014.
- Wikipedia Extractor [https://github.com/bwbaugh/wikipedia-extractor]