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Norman: Normalized PENMAN (AMR)

This is the code associated with the paper AMR Normalization for Fairer Evaluation.

If you are interested in using the normalization procedures with AMR, the 0.7 version of the Penman project incorporates the methods described by the paper. This repository is for reproducing the experiments of the paper.

Citation

@inproceedings{Goodman:2019,
  title     = "{AMR} Normalization for Fairer Evaluation",
  author    = "Goodman, Michael Wayne",
  booktitle = "Proceedings of the 33rd Pacific Asia Conference on Language, Information, and Computation",
  year      = "2019",
  address   = "Hakodate"
}

Running the Experiment

Setup

Python 3.5+ is required to run the experiment. First clone the repository and create a virtual environment, then install norman and its dependencies:

[~]$ git clone https://github.com/goodmami/norman.git
[...]
[~]$ cd norman/
[~/norman]$ python3 -m venv env
[~/norman]$ source env/bin/activate
(env) [~/norman]$ pip install .
[...]

Download the Little Prince corpus v1.6 training data if you don't have it already:

(env) [~/norman]$ mkdir data/
(env) [~/norman]$ wget -P data/ https://amr.isi.edu/download/amr-bank-struct-v1.6-training.txt

For reproducibility, the outputs of JAMR, CAMR, and AMREager used in the paper are included in the sys/ subdirectory, but at this point you may wish to parse with other parsers for additional comparisons.

Normalizing

Call run.sh with --norm, a path to a gold AMR file, and paths to any system outputs.

(env) [~/norman]$ ./run.sh --norm \
> data/amr-bank-struct-v1.6-training.txt \
> sys/amr-bank-struct-v1.6-training.jamr.txt \
> sys/amr-bank-struct-v1.6-training.camr.txt \
> sys/amr-bank-struct-v1.6-training.amr-eager.txt

If you want to modify which tests are performed, inspect run.sh and edit the TESTS variable accordingly. Note that the tests are referenced by keys:

  • i -- canonical role inversion
  • r -- relation reification
  • a -- attribute reification
  • p -- structure preservation

Evaluating

Call run.sh with --eval, a path to a gold AMR file, and paths to any system outputs. Note that these are the paths to the original files, not the normalized ones.

(env) [~/norman]$ ./run.sh --eval \
> data/amr-bank-struct-v1.6-training.txt \
> sys/amr-bank-struct-v1.6-training.jamr.txt \
> sys/amr-bank-struct-v1.6-training.camr.txt \
> sys/amr-bank-struct-v1.6-training.amr-eager.txt

Corpus Statistics

Some of the statistics in the paper regarding the normalizability of the gold and system AMR files were produced using util/corpus-stats.py. Run it (e.g., for the gold file) as follows:

(env) [~/norman]$ python util/corpus-stats.py \
> -r maps/reifications.tsv \
> -c maps/dereifications.tsv \
> data/amr-bank-struct-v1.6-training.txt