.

e2e_nlg.json

@@ -4,10 +4,10 @@
       "has-leaderboard": "no",
       "leaderboard-url": "N/A",
       "leaderboard-description": "N/A",
-      "website": "http://www.macs.hw.ac.uk/InteractionLab/E2E/",
-      "data-url": "https://github.com/tuetschek/e2e-cleaning",
+      "website": "[Website](http://www.macs.hw.ac.uk/InteractionLab/E2E/)",
+      "data-url": "[Github](https://github.com/tuetschek/e2e-cleaning)",
       "paper-url": "[First data release](https://www.aclweb.org/anthology/W17-5525/),   [Detailed E2E Challenge writeup](https://doi.org/10.1016/j.csl.2019.06.009),   [Cleaned E2E version](https://www.aclweb.org/anthology/W19-8652/)",
-      "paper-bibtext": "@inproceedings{e2e_cleaned,\n\taddress = {Tokyo, Japan},\n\ttitle = {Semantic {Noise} {Matters} for {Neural} {Natural} {Language} {Generation}},\n\turl = {https://www.aclweb.org/anthology/W19-8652/},\n\tbooktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},\n\tauthor = {Du\u0161ek, Ond\u0159ej and Howcroft, David M and Rieser, Verena},\n\tyear = {2019},\n\tpages = {421--426},\n}",
+      "paper-bibtext": "```\n@inproceedings{e2e_cleaned,\n\taddress = {Tokyo, Japan},\n\ttitle = {Semantic {Noise} {Matters} for {Neural} {Natural} {Language} {Generation}},\n\turl = {https://www.aclweb.org/anthology/W19-8652/},\n\tbooktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},\n\tauthor = {Du\u0161ek, Ond\u0159ej and Howcroft, David M and Rieser, Verena},\n\tyear = {2019},\n\tpages = {421--426},\n}\n```",
       "contact-name": "Ondrej Dusek",
       "contact-email": "odusek@ufal.mff.cuni.cz"
     },
@@ -40,8 +40,11 @@
       "structure-splits-criteria": "The data are divided so that MRs in different splits do not overlap.\n",
       "structure-description": "n/a",
       "structure-labels": "The source MRs were generated automatically at random from a set of valid attribute values. The labels were crowdsourced and are natural language",
-      "structure-example": "{\n  \"input\":  \"name[Alimentum], area[riverside], familyFriendly[yes], near[Burger King]\",\n  \"target\": \"Alimentum is a kids friendly place in the riverside area near Burger King.\" \n}",
+      "structure-example": "```\n{\n  \"input\":  \"name[Alimentum], area[riverside], familyFriendly[yes], near[Burger King]\",\n  \"target\": \"Alimentum is a kids friendly place in the riverside area near Burger King.\" \n}\n```",
       "structure-outlier": "n/a"
+    },
+    "what": {
+      "dataset": "The E2E NLG dataset is an English benchmark dataset for data-to-text models that verbalize a set of 2-9 key-value attribute pairs in the restaurant domain. The version used for GEM is the cleaned E2E NLG dataset, which filters examples with hallucinations and outputs that don't fully cover all input attributes. "
     }
   },
   "gem": {