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Masters Project

Learning to select cloze questions for KB style question answering

The project file structure follows this general template.

Models can be trained or tested by running main.py with the appropriate command line options, described within the script.

There are four different model classes:

BasicModel - defined in basic_model.py, which uses no generative regularisation (although some mixture of KBP and Cloze data may still be used by varying the generative regularisation strength (lambda) parameter).

ReinforceModelBlackBox - defined in reinforce_model_black_box.py, which uses the cluster based sampler for generative regularisation with the Cloze data.

ReinforceModelBlackBoxReader - defined in reinforce_model_black_box_reader.py, which uses the reader sampler for generative regularisation with the Cloze data.

ReinforceModel - defined in reinforce_model.py, which is not fully implemented but aims to use the standard GeneRe algorithm with the reader sampler.


In order to train these models the data must first be converted to .TFRecords format by running the build_tfrecords_dataset.py and build_categorised_tfrecords_dataset.py scripts. These assume the raw data is stored in the correct directory structure. This must be .../data/raw/[cloze, kbp]/[train, dev, test]/ so as an example the raw kbp training data would be stored in .../data/raw/kbp/train/.


Please contact me at [email protected] if there are any issues running the models or if the data is required.

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