.

cs_restaurants.json

@@ -5,9 +5,9 @@
       "leaderboard-url": "N/A",
       "leaderboard-description": "N/A",
       "website": "n/a",
-      "data-url": "https://github.com/UFAL-DSG/cs_restaurant_dataset",
-      "paper-url": "https://aclanthology.org/W19-8670/",
-      "paper-bibtext": "@inproceedings{cs_restaurants,\n\taddress = {Tokyo, Japan},\n\ttitle = {Neural {Generation} for {Czech}: {Data} and {Baselines}},\n\tshorttitle = {Neural {Generation} for {Czech}},\n\turl = {https://www.aclweb.org/anthology/W19-8670/},\n\turldate = {2019-10-18},\n\tbooktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},\n\tauthor = {Du\u0161ek, Ond\u0159ej and Jur\u010d\u00ed\u010dek, Filip},\n\tmonth = oct,\n\tyear = {2019},\n\tpages = {563--574},\n}",
+      "data-url": "[Github](https://github.com/UFAL-DSG/cs_restaurant_dataset)",
+      "paper-url": "[Github](https://aclanthology.org/W19-8670/)",
+      "paper-bibtext": "```\n@inproceedings{cs_restaurants,\n\taddress = {Tokyo, Japan},\n\ttitle = {Neural {Generation} for {Czech}: {Data} and {Baselines}},\n\tshorttitle = {Neural {Generation} for {Czech}},\n\turl = {https://www.aclweb.org/anthology/W19-8670/},\n\turldate = {2019-10-18},\n\tbooktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},\n\tauthor = {Du\u0161ek, Ond\u0159ej and Jur\u010d\u00ed\u010dek, Filip},\n\tmonth = oct,\n\tyear = {2019},\n\tpages = {563--574},\n}\n```",
       "contact-name": "Ondrej Dusek",
       "contact-email": "odusek@ufal.mff.cuni.cz"
     },
@@ -42,6 +42,9 @@
       "structure-labels": "The input MRs were collected from [Wen et al.'s SF restaurant](https://www.aclweb.org/anthology/D15-1199/) NLG data\nand localized by randomly replacing slot values (using a list of Prague restaurant names, neighborhoods etc.).\n\nThe generated slot values were then automatically replaced in reference texts in the data.\n",
       "structure-splits-criteria": "The creators ensured that after delexicalization of the meaning representation there was no overlap between training and test. \n\nThe data is split at a 3:1:1 rate between training, validation, and test.",
       "structure-outlier": "n/a"
+    },
+    "what": {
+      "dataset": "The Czech Restaurants dataset is a task oriented dialog dataset in which a model needs to verbalize a response that a service agent could provide which is specified through a series of dialog acts. The dataset originated as a translation of an English dataset to test the generation capabilities of an NLG system on a highly morphologically rich language like Czech. "
     }
   },
   "curation": {