Loading README.md +11 −10 Original line number Diff line number Diff line Loading @@ -53,16 +53,16 @@ To work, we use the steps provided by Debjit Paul from Ranking and Selecting Mul ### *Step 1:* Construct ConceptNet into a graph Prerequisite for this step is the previous download of the concept-net-assertions-5.6.0.csz.gz. ``` python src/graph_model/conceptnet2graph.py /path_to_unziped_conceptnet-assertions-5.6.0.csv_File ``` > Inputfile: path to .txtfile of train and testdata > Graphpath: Path to constructed Concepts concept_graph_full <br> > Outputpath: Path to (empty) File, purpose written behind as _[purpose] > Purpose: --dev | --train | --test > > Output is the file concept_graph_full ``` python src/graph_model/conceptnet2graph.py /path_to_unziped_conceptnet-assertions-5.6.0.csv_File ``` ### *Step 2:* Construct subgraph per sentence for for train- test files Loading @@ -72,7 +72,7 @@ In this step we construct the subgraph for each sentence. <br> ``` python src/graph_model/make_sub_graph_server.py "inputfile" "graphpath" "outputpath" "--purpose" purpose <br> e.g. python scr/graph_model/make_sub_graph_server.py .\training_neu.txt .\concept_graph_full .\output --purpose train e.g. python src/graph_model/make_sub_graph_server.py .\training_neu.txt .\concept_graph_full .\output --purpose train ``` Inputformat: ~~~~ Loading @@ -84,7 +84,8 @@ Seperate sentences with newlines. ### *Step 3:* Extracting relevant knowledge paths from subgraphs > Inputpath: path to inputfile from step 2 <br> > Outputpath: path to txt.file where extracted knowledgepaths can be saved <br> > Input: subgraphs and inputfile from step 2<br> > > Input: subgraphs and inputfile from output of step 2<br> > Output: .txtfile with knowledgepaths for each sentence ``` Loading @@ -93,10 +94,10 @@ python src/graph_model/extract_path3.py ## Authors * Jasikka Pirapakaran * Ufkun Menderes * Dorian Heide * Stefanie Kühner * Jasikka Pirapakaran - pirapakaran@cl.uni-heidelberg.de * Ufkun Menderes - menderes@cl.uni-heidelberg.de * Dorian Heide - heide@cl.uni-heidelberg.de * Stefanie Kühner - kuehner@cl.uni-heidelberg.de ## Acknowledgments Loading Loading
README.md +11 −10 Original line number Diff line number Diff line Loading @@ -53,16 +53,16 @@ To work, we use the steps provided by Debjit Paul from Ranking and Selecting Mul ### *Step 1:* Construct ConceptNet into a graph Prerequisite for this step is the previous download of the concept-net-assertions-5.6.0.csz.gz. ``` python src/graph_model/conceptnet2graph.py /path_to_unziped_conceptnet-assertions-5.6.0.csv_File ``` > Inputfile: path to .txtfile of train and testdata > Graphpath: Path to constructed Concepts concept_graph_full <br> > Outputpath: Path to (empty) File, purpose written behind as _[purpose] > Purpose: --dev | --train | --test > > Output is the file concept_graph_full ``` python src/graph_model/conceptnet2graph.py /path_to_unziped_conceptnet-assertions-5.6.0.csv_File ``` ### *Step 2:* Construct subgraph per sentence for for train- test files Loading @@ -72,7 +72,7 @@ In this step we construct the subgraph for each sentence. <br> ``` python src/graph_model/make_sub_graph_server.py "inputfile" "graphpath" "outputpath" "--purpose" purpose <br> e.g. python scr/graph_model/make_sub_graph_server.py .\training_neu.txt .\concept_graph_full .\output --purpose train e.g. python src/graph_model/make_sub_graph_server.py .\training_neu.txt .\concept_graph_full .\output --purpose train ``` Inputformat: ~~~~ Loading @@ -84,7 +84,8 @@ Seperate sentences with newlines. ### *Step 3:* Extracting relevant knowledge paths from subgraphs > Inputpath: path to inputfile from step 2 <br> > Outputpath: path to txt.file where extracted knowledgepaths can be saved <br> > Input: subgraphs and inputfile from step 2<br> > > Input: subgraphs and inputfile from output of step 2<br> > Output: .txtfile with knowledgepaths for each sentence ``` Loading @@ -93,10 +94,10 @@ python src/graph_model/extract_path3.py ## Authors * Jasikka Pirapakaran * Ufkun Menderes * Dorian Heide * Stefanie Kühner * Jasikka Pirapakaran - pirapakaran@cl.uni-heidelberg.de * Ufkun Menderes - menderes@cl.uni-heidelberg.de * Dorian Heide - heide@cl.uni-heidelberg.de * Stefanie Kühner - kuehner@cl.uni-heidelberg.de ## Acknowledgments Loading