Merge pull request #1 from Priberam/master

Update

README.md

@@ -1,4 +1,8 @@
-# Under Construction - please wait# ExCoNSumm :Jointly Extracting and Compressing Documentswith Summary State Representations
+
+# Under Construction - please wait
+
+# ExCoNSumm :Jointly Extracting and Compressing Documentswith Summary State Representations
+
 
 This repository releases our code for ExConSum. It uses dynet and the code is in C++.
 
@@ -10,19 +14,19 @@ Please contact afonso@priberam.com or sebastiao@priberam.com for any question.
 
 The datasets and the word emebeddings are the same as for REFRESH except for the compressed version. You can get them from https://github.com/EdinburghNLP/Refresh.
 
-The Compressive Oracles dataset used in the paper are available at:
+The Compressive and extactive Oracles dataset used in the paper are available at:
 
 ```
 wget ftp://"ftp.priberam.pt|anonymous"@ftp.priberam.pt/SUMMAPublic/Corpora/Exconsumm/ExCoNSum-CNN-DailyMail-Data.tgz
 ```
 
 ### Training
 
-./exconsumm -ccnndm.cfg -t --dynet-autobatch 1 --dynet-mem 7500
+./exconsumm -cconfig/extractive_cnn.cfg -t --dynet-autobatch 1 --dynet-mem 7500
 
 ### Evaluation
 
-./exconsumm -ccnndm.cfg -t --dynet-autobatch 1 --dynet-mem 7500
+./exconsumm -coutput/.cfg  --dynet-autobatch 1 --dynet-mem 7500
 
 ### Build the system
 

exconsumm/Corpus.cpp

@@ -635,8 +635,6 @@ void Document::OutputSummary(const std::vector<int>& sentences_actions, const st
             }
         }
 
-    std::ofstream asumr_file(path + ".asum");
-    asumr_file << abstractive_summary << std::endl;
 }
 
 

exconsumm/NeuralSummarization.cpp

@@ -194,7 +194,6 @@ int main(int argc, char** argv)
 
       model_config->Logger("csum") << "Output path: " << output_path << std::endl;
       model_config->Logger("gsum") << "Output path: " << output_path << std::endl;
-      model_config->Logger("asum") << "Output path: " << output_path << std::endl;
 
       validation_corpus->set_keep_words(true);
 
@@ -287,7 +286,6 @@ int main(int argc, char** argv)
 
       model_config->Logger("csum") << "Output path: " << output_path << std::endl;
       model_config->Logger("gsum") << "Output path: " << output_path << std::endl;
-      model_config->Logger("asum") << "Output path: " << output_path << std::endl;
 
       model_config->vocab_size((unsigned)data_model.words().m_str_vec.size());
       model_config->action_size((unsigned)data_model.actions().size());