The DBpedia Data Set

Link: http://wiki.dbpedia.org/Datasets

Intro: The DBpedia data set uses a large multi-domain ontology which has been derived from Wikipedia. The English version of the DBpedia data set currently describes 3.77 million “things” with 400 million “facts”.

Explicit Semantic Analysis - ESA

Intro: ESA is a vector representation of texts based on Wikippedia as external knowledge base.
Link: http://www.cs.technion.ac.il/~gabr/resources/code/esa/esa.html

Statistical Methods in Language and Linguistic Research

Link: https://www.equinoxpub.com/equinox/books/showbook.asp?bkid=348&keyword=

String Toolkit for Text Processing

Link: http://www.codeproject.com/Articles/23198/C-String-Toolkit-StrTk-Tokenizer

It can be used as lite version of Boost.

Job markets for NLPers

Link: http://www.nlppeople.com/

Multeval

Link: https://github.com/jhclark/multeval

Intro: MultEval takes machine translation hypotheses from several runs of an optimizer and provides 3 popular metric scores, as well as, standard deviations (via bootstrap resampling) and p-values (via approximate randomization). This allows researchers to mitigate some of the risk of using unstable optimizers such as MERT, MIRA, and MCMC. It is intended to help in evaluating the impact of in-house experimental variations on translation quality; it is currently not setup to do bake-off style comparisons (bake-offs can't require multiple optimizer runs nor a standard tokenization).

Related: http://www.ark.cs.cmu.edu/MT/ (Code for Statistical Significance Testing for MT Evaluation Metrics)

MacPorts

Link: http://www.macports.org/index.php

Intro: The MacPorts Project is an open-source community initiative to design an easy-to-use system for compiling, installing, and upgrading either command-line, X11 or Aqua based open-source software on the Mac OS X operating system. To that end we provide the command-line driven MacPorts software package under a BSD License, and through it easy access to thousands of ports that greatly simplify the task of compiling and installing open-source software on your Mac.