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55## Overview
66The code is organized as notebooks, to be used as follows:
7- * ` final_generate_gazetteers.ipynb ` : to generate the gazeteers from Wikidata (by specifying a list of QIDs correspoding to the classes)
7+ * ` final_generate_gazetteers.ipynb ` : to generate the gazeteers from Wikidata (by specifying a list of QIDs corresponding to the classes)
88* ` edge_list_generation.ipynb ` : to generate the graph structure to build the graph embeddings
99* ` graph_embeddings_generation.ipynb ` : to generate node embeddings using [ GEM library] ( https://github.com/palash1992/GEM ) algorithms (e.g. node2ve, SDNE..)
1010* ` nodes_classifier.ipynb ` : to train a model for the node embeddings
11- * ` autoencoder_embeddings.ipynb ` : to generate auto-encoder embeddings from the binary graph representations.
11+ * ` autoencoder_embeddings.ipynb ` : to generate auto-encoder embeddings from the binary graph representations
1212* ` autoencoder_nn_classification.ipynb ` : to train a model for the auto-encoder embeddings
1313* ` GCN-node-simple-features.ipynb ` : to train a GCN on the CoNLL-2003 task
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