Open Domain Question Answering (ODQA) is a task to find an exact answer to any question in Wikipedia articles. Thus, given only a question, the system outputs the best answer it can find:
What is the name of Darth Vader’s son?
There are pretrained ODQA models for English and Russian languages in DeepPavlov.
The architecture of ODQA skill is modular and consists of two models, a ranker and a reader. The ranker is based on DrQa proposed by Facebook Research (Reading Wikipedia to Answer Open-Domain Questions) and the reader is based on R-Net proposed by Microsoft Research Asia (“R-NET: Machine Reading Comprehension with Self-matching Networks”) and its implementation by Wenxuan Zhou.
Tensorflow-1.8.0 with GPU support is required to run this model.
About 16 GB of RAM required
When interacted, the ODQA model returns a plain answer to the user’s question.
Run the following to interact English ODQA:
cd deeppavlov/ python deep.py interact deeppavlov/configs/odqa/en_odqa_infer_wiki.json -d
Run the following to interact the ranker:
cd deeppavlov/ python deep.py interact deeppavlov/configs/odqa/ru_odqa_infer_wiki.json -d