Machine translation (MT) quality estimation (QE) open source system that implements feature extractors for all or most of the information sources used in systems submitted to the shared task, and possibly new features, and that can be customized to particular applications.

The libraries required to compile and run the code are included in the "lib" directory in the root directory of the distribution. The Java libraries should be included there when possible. Here is a list of libraries that should be downloaded and placed in the "lib" directory:

• Stanford POS Tagger ( http://nlp.stanford.edu/software/tagger.shtml#Download )

Features extend an abstract class called "Feature". From the class documentation:

" Feature is an abstract class which models a sentence feature. Typically, a Feature consist of a value, a procedure for calculating the value and a set of dependencies, i.e., resources that need to be available in order to be able to compute the feature value.
Classes extending Feature will have to provide their own method for computing the feature value by implementing run() "

Each feature should provide a set with the name of the resources (external linguistics processors that run in the preprocessing step) required to process the feature. The resources are managed by a class called ResourceManager that keeps track of the resources currently handled by the system.

If a system requires a resource that has not been registered/processed previously, it is necessary to create a wrapper that implements and registers it.

Different preprocessors extend the abstract class "Resource". One example is the Tokenizer class that implements a wrapper for the Moses tokenizer:

src/wlv/mt/tools/Tokenizer.java

The extended classes usually run the external code by spawning a new process (using Java's ProcessBuilder class). The results can then be retrieved in the form of output files by the Java code. More examples of different cases are in src/wlv/mt/tools/

More information about implementation can be found in the MTFeatures.docx development guide file:

https://github.com/lspecia/quest/blob/master/doc/MTFeatures.docx