| # TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension | |
| - This repo contains code for the paper | |
| Mandar Joshi, Eunsol Choi, Daniel Weld, Luke Zettlemoyer. | |
| [TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension][triviaqa-arxiv] | |
| In Association for Computational Linguistics (ACL) 2017, Vancouver, Canada. | |
| - The data can be downloaded from the [TriviaQA website][triviaqa-website]. The Apache 2.0 License applies to both the code and the data. | |
| - Please contact [Mandar Joshi][mandar-home] (\<first-name\>90@cs.washington.edu) for suggestions and comments. | |
| ## Requirements | |
| #### General | |
| - Python 3. You should be able to run the evaluation scripts using Python 2.7 if you take care of unicode in ```utils.utils.py```. | |
| - BiDAF requires Python 3 -- check the [original repository][bidaf-orig-github] for more details. | |
| #### Python Packages | |
| - tensorflow (only if you want to run BiDAF, verified on r0.11) | |
| - nltk | |
| - tqdm | |
| ## Evaluation | |
| The ```dataset file``` parameter refers to files in the ```qa``` directory of the data (e.g., ```wikipedia-dev.json```). For file format, check out the ```sample``` directory in the repo. | |
| ``` | |
| python3 -m evaluation.triviaqa_evaluation --dataset_file samples/triviaqa_sample.json --prediction_file samples/sample_predictions.json | |
| ``` | |
| ## Miscellaneous | |
| - If you have a SQuAD model and want to run on TriviaQA, please refer to ```utils.convert_to_squad_format.py``` | |
| [bidaf-orig-github]: https://github.com/allenai/bi-att-flow/ | |
| [triviaqa-arxiv]: https://arxiv.org/abs/1705.03551 | |
| [mandar-home]: http://homes.cs.washington.edu/~mandar90/ | |
| [triviaqa-website]: http://nlp.cs.washington.edu/triviaqa/ | |