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interp

Preprocessing (LSTM / GloVe weights)

LSTM

  1. prepro.py train.txt test.txt 0 convert/train_parsed.txt convert/test_parsed.txt 20 35 convert/data

  2. model.lua [ >> checkpoint/lm_... ]

  3. get_states.lua [ >> checkpoint/lstm_states.h5 ]

  4. get_lookuptable.lua [ >> embeddings/lstm_LT.h5 ]

GloVe

  1. prepro_word.py train.txt test.txt 0 convert_word/train_parsed.txt convert_word/test_parsed.txt convert_word/data

  2. load_glove.py N convert_word/data.targ.dict [ >> embeddings/gloveN.hdf5 ]

Pipeline (LSTM States)

  1. prepro_chunks.py convert/train_parsed_chunks.txt 0 convert/train_parsed_chunks.dict

  2. tempconv.lua [ >> test_results.hdf5 ]

  3. postpro_conll.py test.txt convert/train_parsed_chunks.dict test_results.hdf5 test_conll.txt

  4. ./conlleval.pl < test_conll.txt

Pipeline (Word)

  1. tempconv_word.lua [ >> word_test_results.hdf5 ]

  2. postpro_conll.py test.txt convert/train_parsed_chunks.dict word_test_results.hdf5 test_conll_word.txt

  3. ./conlleval.pl < test_conll_word.txt

Pipeline (Sequencer, LSTM States)

  1. sequencer_prepro.py train.txt test.txt convert_seq/data

  2. sequencer_model.lua

  3. sequencer_get_states.lua

  4. sequencer_tempconv.lua

  5. sequencer_postpro.py sequencer_test.txt convert_seq/train_parsed_chunks.dict sequencer_test_results.hdf5 sequencer_test_conll.txt 1

  6. ./conlleval.pl < sequencer_test_conll.txt

Pipeline (Sequencer, Word)

  1. sequencer_prepro.py train.txt test.txt convert_seq/data

  2. sequencer_tempconv_word.lua

Pipeline (POS)

  1. tempconv.lua [ >> test_results_pos.hdf5 ('output' = predicted tags, 'chunks' = actual tags) ]

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