This is the implementation of word aligner using Hidden Markov Model
A General Purpose Tagger for POS Tagging, NER Tagging, and Chunking.
website for the SFU natural language lab
Joint prediction of word alignment with alignment types
Simple macros for converting bracketed trees into LaTeX STAG tree-pairs.
Visualize bilingual word embeddings.
Tree-adjoining grammar based statistical dependency parser using a general linear model (glm).
Lensing Wikipedia is an interface to visually browse through human history as represented in Wikipedia. This the source code that runs the website:
The program used in the paper 'Gut, Besser, Chunker – Selecting the best models for text chunking with voting' by Balázs Indig and István Endrédy
Website for the TAG+9 workshop.
Left to right decoding for Hiero Statistical Machine Translation
The XTAG English Grammar mirrored from the XTAG page http://www.cis.upenn.edu/~xtag/
The original SS05 algorithm from Hong Shen and Anoop Sarkar used in the paper 'Voting Between Multiple Data Representations for Text Chunking'
website for the North West NLP conference 2014
Metaphor dataset: literal versus non-literal uses of words
use typed alignment links to improve word alignment
Code for multi-lingual alignment using HMMs
Constrain HMM with graph propagation
Decipherment by marching crib text across to solve (simple) substitution ciphers.
Python code for phrase extraction and different types of SCFG rule extraction from word aligned parallel data.
Graph propagation for statistical machine translation
Python module for working with the Penn Treebank
Hierarchical phrase-based machine translation system
This repository provides codes required for testing hadoop functionality.
Python code to read, display and parse with the XTAG English (and other) grammars as part of the NLTK project.
Use Vickrey-Koller simplification rules for semantic role labeling
Korean grammar in the Tree Adjoining Grammar framework developed as part of the XTAG project at UPenn.