Loading Readme.md +9 −7 Changes for Readme.md: 9 added lines, 7 removed lines. Original line number Diff line number Diff line Loading @@ -12,21 +12,21 @@ predicts 33 accuracy metrics for a given sentence and its (automatic) AMR parse cd src ./split_into_single_files.sh ./run_full_eval.sh ''' ``` 2. Now we prepare training, dev and test json-files ``` cd src python create_data_dicts.py ''' ``` Now we train a toy model (which will be bad because of the small data) ``` cd src python quamr_dep.py exampledict-gold.json.train,exampledict-camr.json.train,exampledict-jamr.json.train,exampledict-gpla.json.train exampledict-gold.json.dev,exampledict-camr.json.dev,exampledict-jamr.json.dev,exampledict-gpla.json.dev exampledict-gold.json.train,exampledict-camr.json.test,exampledict-jamr.json.test,exampledict-gpla.json.test 99 1 ''' ``` training dev and testing data are separated with space. 99 is some run-index and 1 refers to a specifig setup in config.py Loading @@ -41,20 +41,21 @@ each AMR must have a \# snt:: line which is the orig. sentence of the correspond ``` cd src python create_data_dict_for_prediction.py INPUTFILE OUTPUTFILE ''' ``` for example ``` cd src python create_data_dict_for_prediction.py ../data/test/exampledata-gpla.txt gpla-parses.json ''' ``` A pretrained model can be found in src/models, now we can predict the accuracies ``` cd src python -u quamr_dep_predict.py gpla-parses.json 0 1 ''' ``` 0 is the model index of the pretrained model (I put one under src/models/) and 1 is the config setup Loading @@ -62,6 +63,7 @@ this prints out json lines with predicted accuracies which can be used e.g., for ### Citation ``` @inproceedings{opitzfrank:2019b, author = {Juri Opitz and Anette Frank}, Loading @@ -72,4 +74,4 @@ this prints out json lines with predicted accuracies which can be used e.g., for note = {to appear}, url = {https://arxiv.org/abs/1904.08301v1} } ''' ``` Loading
Readme.md +9 −7 Changes for Readme.md: 9 added lines, 7 removed lines. Original line number Diff line number Diff line Loading @@ -12,21 +12,21 @@ predicts 33 accuracy metrics for a given sentence and its (automatic) AMR parse cd src ./split_into_single_files.sh ./run_full_eval.sh ''' ``` 2. Now we prepare training, dev and test json-files ``` cd src python create_data_dicts.py ''' ``` Now we train a toy model (which will be bad because of the small data) ``` cd src python quamr_dep.py exampledict-gold.json.train,exampledict-camr.json.train,exampledict-jamr.json.train,exampledict-gpla.json.train exampledict-gold.json.dev,exampledict-camr.json.dev,exampledict-jamr.json.dev,exampledict-gpla.json.dev exampledict-gold.json.train,exampledict-camr.json.test,exampledict-jamr.json.test,exampledict-gpla.json.test 99 1 ''' ``` training dev and testing data are separated with space. 99 is some run-index and 1 refers to a specifig setup in config.py Loading @@ -41,20 +41,21 @@ each AMR must have a \# snt:: line which is the orig. sentence of the correspond ``` cd src python create_data_dict_for_prediction.py INPUTFILE OUTPUTFILE ''' ``` for example ``` cd src python create_data_dict_for_prediction.py ../data/test/exampledata-gpla.txt gpla-parses.json ''' ``` A pretrained model can be found in src/models, now we can predict the accuracies ``` cd src python -u quamr_dep_predict.py gpla-parses.json 0 1 ''' ``` 0 is the model index of the pretrained model (I put one under src/models/) and 1 is the config setup Loading @@ -62,6 +63,7 @@ this prints out json lines with predicted accuracies which can be used e.g., for ### Citation ``` @inproceedings{opitzfrank:2019b, author = {Juri Opitz and Anette Frank}, Loading @@ -72,4 +74,4 @@ this prints out json lines with predicted accuracies which can be used e.g., for note = {to appear}, url = {https://arxiv.org/abs/1904.08301v1} } ''' ```
