WordSegmentation

The task for this project is to segment a sequence of English characters into the most likely word sequence.

This is mainly to set up your groups and programming environment

Installation

Make sure you setup your virtual environment:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

You can optionally copy and modify the requirements for when we test your code:

cp requirements.txt answer/requirements.txt

Required files

You must create the following files:

answer/ensegment.py
answer/ensegment.ipynb

Create output.zip

To create the output.zip file for upload to Coursys do:

python3 zipout.py

For more options:

python3 zipout.py -h

Create source.zip

To create the source.zip file for upload to Coursys do:

python3 zipsrc.py

For more options:

python3 zipsrc.py -h

Check your accuracy

To check your accuracy on the dev set:

python3 check.py

For more options:

python3 check.py -h

In particular use the log file to check your output evaluation:

python3 check.py -l log

The accuracy on data/input/test.txt will not be shown. We will evaluate your output on the test input after the submission deadline.

Default solution

The default solution is provided in default.py. To use the default as your solution:

cp default.py answer/ensegment.py
cp default.ipynb answer/ensegment.ipynb
python3 zipout.py
python3 check.py

Make sure that the command line options are kept as they are in default.py. You can add to them but you must not delete any command line options that exist in default.py.

Submitting the default solution without modification will get you zero marks.

Data files

The data files provided are:

• data/count_1w.txt -- counts taken from the Google n-gram corpus with 1TB tokens
• data/input -- input files dev.txt and test.txt
• data/reference/dev.out -- the reference output for the dev.txt input file