DBpedia Neural Multilingual QA - GSoC project summery
GSoC blog This blog includes a detailed description of the work I carried out during the GSoC period. The above mentioned blog includes the tasks carried out on a weekly basis. Brief Description of my work Implement airML using KBox and pip. This task was to create and distribute KBox into a pip package called airML, which will allow users to share and dereference ML models Share the Monument dataset with airML. Train the monument dataset and place it in a public repository and dereference it with airML. Create the language detector dataset. Iterate over all questions in IRbench , creating the dataset. Create a language detector model and train it. After creating the model, I evaluated other existing language models and wrote a research paper with my mentor. Experimentation in Machine Translation methods. Creating datasets. Annotating Datasets. Evaluating different methods. The full description of Tasks carried out and the obtained results are included in this blog . The results ob