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.