AMR-EAGER is a transition-based parser for Abstract Meaning Representation. For more details, visit https://github.com/mdtux89/amr-eager

To download the trained models, run the following script

./download.sh

• Install JAMR aligner (https://github.com/jflanigan/jamr) and set path in preprocessing-pt.sh

• PALAVRAS Parser (http://visl.sdu.dk/constraint_grammar.html)
• NLTK (http://www.nltk.org/)

The input data format for parsing should be raw document with one sentence per line. See example/test.txt

First, run preprocessing

python3 preprocessing-pt.py

and

./preprocessing_pt.sh

This will give you output files in the same directory with the prefix <sentences_file> and extensions .out and .sentences.

Then, run

python preprocessing.py -f <sentences_file>

This will give you output files in the same directory with the prefix <sentences_fileand extensions .tokens.p and .dependencies.p

Then, run the parser

python parser.py -f <file> -m <model_dir>

This will give you the parsed AMR file (.parsed) in the same directory as your input sentence file.