What is QANUS about?


QANUS is an abbreviation for Question-Answering by NUS, NUS being the abbreviation of the National University of Singapore. QANUS is an open-sourced, information-retrieval (IR) based question-answering (QA) system.

There are 2 key motivating factors behind the development of QANUS.

  1.  Serve as a framework from which QA systems can be quickly developed.
  2. Act as a baseline system against which QA performance can be easily and reproducibly benchmarked.

Extensible Framework

QANUS is a pipelined QA system. It is designed from the ground-up to be easily extendable. This allows QANUS to serve as a good starting point from which ideas and technologies can be quickly tested andvalidated.

QANUS is shipped with many of the common techniques used for state-of-the-art QA, including modules for named entity recognition, part-of-speech tagging and question classification. As new techniques mature, these can be easily incorporated into QANUS.

It is easy to customise QANUS to different datasets and techniques by adding/removing input/output modules, or text processing modules as needed. More information can be obtained from the documentation for QANUS.

Reproducible Benchmark

The open-source nature of the system will allow researchers to reliably reproduce experimental results which can serve as a baseline for more advanced and complex QA systems.

It is usually hard to validate the performance of various QA systems and technologies as many systems are proprietary and not freely available to the community. QANUS gives the community access to a common system against which to benchmark new QA systems.

Currently performance is typically measured relative to results from part TREC QA tracks. However these previous results are static, and do not reflect the general performance of the state-of-the-art as the years roll by.

As the field advances, QANUS will be kept updated with the latest technological advances and thus can be kept relevant. This will allow new systems to reproducibly validate their performance against an up-to-date QA system.