Adding language to QA scenario readme #bender rule
@@ -16,8 +16,8 @@ of Bidirectional Recurrent Neural Networks (BRNN).
## Summary
-|Notebook|Environment|Description|Dataset
-|---|---|---|---|
-|[Deployed QA System in Under 20 minutes](question_answering_system_bidaf_quickstart.ipynb)|Azure Container Instances| Learn how to deploy a QA system in under 20 minutes using Azure Container Instances (ACI) and a popular AllenNLP pre-trained model called BiDAF.|[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/)|
-|[BiDAF Deep Dive](bidaf_aml_deep_dive.ipynb)|Azure ML| Learn about the architecture of the BiDAF model and how to train it from scratch using the AllenNLP library on the AzureML platform.|[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/)
-|[Pretrained BERT SQuAD Deep Dive](pretrained-BERT-SQuAD-deep-dive-aml.ipynb)|Azure ML| Learn about the mechanism of the BERT model in an end to end pipeline on the AzureML platform and how to fine tune it from scratch using the distributed training with Horovod. Show the improvement on the model performance using hyper-parameter tuning|[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/)|
+|Notebook|Environment|Description|Dataset | Language
+|---|---|---|---|----|
+|[Deployed QA System in Under 20 minutes](question_answering_system_bidaf_quickstart.ipynb)|Azure Container Instances| Learn how to deploy a QA system in under 20 minutes using Azure Container Instances (ACI) and a popular AllenNLP pre-trained model called BiDAF.|[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/)| English |
+|[BiDAF Deep Dive](bidaf_aml_deep_dive.ipynb)|Azure ML| Learn about the architecture of the BiDAF model and how to train it from scratch using the AllenNLP library on the AzureML platform.|[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) | English |
+|[Pretrained BERT SQuAD Deep Dive](pretrained-BERT-SQuAD-deep-dive-aml.ipynb)|Azure ML| Learn about the mechanism of the BERT model in an end to end pipeline on the AzureML platform and how to fine tune it from scratch using the distributed training with Horovod. Show the improvement on the model performance using hyper-parameter tuning|[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/)| English |
