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Cross-lingual Simple Question Answering with Memory Networks

Prepare dataset and knowledge base

python3 ./data_prepared/summarize_corpus.py

python3 ./data_prepared/summarize_facts.py

python3 ./data_prepared/divide_corpus.py

Train MemNN

python3 SQA.py

continue training MemNN with saved checkpoint

python3 SQA.py --from_checkpoint True

Test MemNN

python3 SQA.py --state 1 --from_checkpoint True

QA with trained MemNN

python3 SQA.py --state 2 --from_checkpoint True

folders and files

/checkpoint :

the default folder to save checkpoint of MemNN

/corpus :

/original:

    the original datasets

sum_corpus.txt:

     default file which collect all dataset in /original folder

testset.txt: 

    default test dataset

trainset.txt: 

    default train dataset

/data_prepared :

divide_corpus.py:

    divide the /corpus/sum_corpus.txt to /corpus/trainset.txt and /corpus/testset.txt

summarize_corpus.py:

    summarize dataset in /corpus/original in /corpus/sum_corpus.txt

summarize_fact.py:

    summarize knowledge base in /facts/original in /corpus/sum_facts.txt

/facts :

/original:

    the original knowledge base

sum_facts.txt:

    default file which collect all knowledge base in /original folder

/intermediate:

save intermediate files generated in training process and used in test/answer process

/MemNN:

MemNN and its components

/transform:

json object which could map mid/IMDBid to labels and map labels to mid/IMDBid

common.py

SQA.py:

main file of the project

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