CAMR Parser adapted to Portuguese

CARM is a transition-based, tree-to-graph parser for the Abstract Meaning Representation of a sentence. For more details, visit https://github.com/c-amr/camr

Trained Models

To download the trained models, run the following script

./download.sh

Dependencies

• PALAVRAS Parser (http://visl.sdu.dk/constraint_grammar.html)
• NLTK (http://www.nltk.org/)
• NLPNET (http://nilc.icmc.sc.usp.br/nlpnet/)

Parsing with Pre-Trained Model (Little Prince)

The input data format for parsing should be raw document with one sentence per line.

First, run preprocessing

python3 wang_preprocessing.py -f <input_sentence_file>

This will give you the tokenized sentences (.tok), POS tag and name entity (.prp), and dependency structure (.charniak.parse.dep)

Then, run the parser

python amr_parsing.py -m parse --model <model_file> <input_sentence_file> 2>log/error.log

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