the source code and the solution-modules

[dinani65]

The main code includes 3 folders: RoBERTa, LSTM and train_embeddings and the paper-solution contains four main steps: KG embedding, Question embedding, Answer selection and Relation matching.
As far as I have understood, Relation matching has not been implemented, LSTM is related to question embedding for MetaQA dataset, RoBERTa is related to WebQSP dataset. what about the train_embeddings folder?
Could u please explain more regarding the relations between codes and the modules of the solution?

[jishnujayakumar]

It is used for training MetaQA KG dataset whereas LibKGE is used for training WebQSP KG dataset. Two different methods are used for the two KG datasets. For further information, visit here.

[XLR81999]

I have a further query on this, did you try RoBERTa implementation on MetaQA dataset? My implementation had huge training time with really bad accuracy

[jishnujayakumar]

No, we didn't try RoBERTa on the MetaQA dataset.

[dinani65]

I do apologize it due to my question is not related to the topic but I would greatly happy if u can answer.
what is the best and fast way to generate embeddings of some freebase-IDs (e.g. RDF2Vec technique)? Do I have to download the whole freebase dataset at first and use a graph database?