This repo contains the scripts for conducting human evaluation for data2text generation

Summary Ranking

Generate the csv for MLB:

python summary_ranking_mlb.py -gold data/mlb/gold.txt \
        -template data/mlb/template.txt \
        -macro data/mlb/macro.txt \
        -ent data/mlb/ent.txt \
        -ed_cc data/mlb/ent.txt \
        -output_file data/outputs/mlb.csv

Generate the csv for RotoWire:

python summary_ranking_rotowire.py -gold data/rotowire/gold.txt \
        -template data/rotowire/template.txt \
        -macro data/rotowire/macro.txt \
        -hier data/rotowire/hier.txt \
        -ed_cc data/rotowire/ed_cc.txt \
        -output_file data/outputs/rotowire.csv

Fact Counting

Generate the csv for MLB:

python fact_verification_mlb.py -input_path data/test_json/mlb_test.json  \
    -gold data/mlb/gold.txt \
    -template data/mlb/template.txt \
    -macro data/mlb/macro.txt \
    -ent data/mlb/ent.txt \
    -ed_cc data/mlb/ed_cc.txt \
    -output_file data/outputs/mlb_fact.csv

Generate the csv for RotoWire:

python fact_verification_rotowire.py -input_path data/test_json/rotowire_test.json \
    -gold data/rotowire/gold.txt \
    -template data/rotowire/template.txt \
    -macro data/rotowire/macro.txt \
    -hier data/rotowire/hier.txt \
    -ed_cc data/rotowire/ed_cc.txt \
    -output_file data/outputs/rotowire_fact.csv

Acknowledgements

Some code for creating the input tables using pandas for RotoWire dataset is due to @swiseman.