Work in progress
Guided Neural Language Generation for Abstractive Summarization Using AMR
This repository contains code for our EMNLP 2018 paper "Guided Neural Language Generation for Abstractive Summarization Using AMR"
Obtaining the Dataset
We used the Abstract Meaning Representation Annotation Release 2.0 which contains manually annotated document and summary AMR.
Preprocessing the Data
For preprocessing, clone the AMR preprocessing repository.
git clone https://github.com/sheffieldnlp/AMR-Preprocessing
Run the AMR linearizing where the input is the system summary AMR from Liu's summarizer ($F) and the AMR raw dataset ($AMR). Here we use the test dataset. Run the preprocessing on the training, and validation dataset if you want to train the model.
export F_TRAIN=//amr-release-2.0-amrs-training.txt
export F_TEST=//amr-release-2.0-amrs-test.txt
export F_DEV=//amr-release-2.0-amrs-dev.txt
export OUTPUT=/ For each set (train, test and dev) the script will produce a set of two files: the sentence (.sent) and its respective linearized AMR (.tf) files.
Training New Model
export SRC=//all_amr-release-2.0-amrs-training.txt.tf
export TGT=//all_amr-release-2.0-amrs-training.txt.sent
export SRC_VALID=//all_amr-release-2-0-amrs-dev-all.txt.tf
export TGT_VALID=//all_amr-release-2-0-amrs-dev-all.txt.sent
export SAVE=//
python preprocess.py -train_src $SRC -train_tgt $TGT -valid_src $SRC_VALID -valid_tgt $TGT_VALID -save_data $SAVE -src_seq_length 1000 -tgt_seq_length 1000 -shuffle 1
export F=//summ_ramp_10_passes_len_edges_exp_0
export OUTPUT=/
export AMR=//amr-release-2.0-amrs-test-proxy.txt
python var_free_amrs.py -is_dir -f $F -output_path $OUTPUT --custom_parentheses --no_semantics --delete_amr_var --with_side -side_file $AMR
python $WORK/train.py -data $PREPROCESS/van_noord/no_filter_amr_2/data -save_model $MODEL/$TYPE -rnn_size 500 -layers 2 -epochs 2000 -optim sgd -learning_rate 1 -learning_rate_decay 0.8 -encoder_type brnn -global_attention general -seed 1 -dropout 0.5 -batch_size 32
Generation with New Model
python $WORK/translate.py -src $file -output