Fix and add info

README.md

@@ -21,6 +21,33 @@ tags:
 task_categories:
 - translation
 task_ids: []
+dataset_info:
+  features:
+  - name: id
+    dtype: int32
+  - name: context_en
+    dtype: string
+  - name: en
+    dtype: string
+  - name: context_fr
+    dtype: string
+  - name: fr
+    dtype: string
+  - name: has_supporting_context
+    dtype: bool
+  config_name: sentences
+  splits:
+  - name: train
+    num_bytes: 6813668
+    num_examples: 11144
+  - name: validation
+    num_bytes: 93178
+    num_examples: 144
+  - name: test
+    num_bytes: 583831
+    num_examples: 973
+  download_size: 7292968
+  dataset_size: 7490677
 ---
 
 # Dataset Card for SCAT

dataset_info.json

@@ -0,0 +1,113 @@
+{
+    "description": "The Supporting Context for Ambiguous Translations corpus (SCAT) is a dataset \nof English-to-French translations annotated with human rationales used for resolving ambiguity \nin pronoun anaphora resolution for multi-sentence translation.\n",
+    "citation": "@inproceedings{yin-etal-2021-context,\n    title = \"Do Context-Aware Translation Models Pay the Right Attention?\",\n    author = \"Yin, Kayo  and\n      Fernandes, Patrick  and\n      Pruthi, Danish  and\n      Chaudhary, Aditi  and\n      Martins, Andr{'e} F. T.  and\n      Neubig, Graham\",\n    booktitle = \"Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)\",\n    month = aug,\n    year = \"2021\",\n    address = \"Online\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2021.acl-long.65\",\n    doi = \"10.18653/v1/2021.acl-long.65\",\n    pages = \"788--801\",\n}\n",
+    "homepage": "https://github.com/neulab/contextual-mt/tree/master/data/scat",
+    "license": "Unknown",
+    "features": {
+      "id": {
+        "dtype": "int32",
+        "_type": "Value"
+      },
+      "context_en": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "en": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "context_fr": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "fr": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "has_supporting_context": {
+        "dtype": "bool",
+        "_type": "Value"
+      }
+    },
+    "builder_name": "scat",
+    "config_name": "sentences",
+    "version": {
+      "version_str": "0.0.0",
+      "major": 0,
+      "minor": 0,
+      "patch": 0
+    },
+    "splits": {
+      "train": {
+        "name": "train",
+        "num_bytes": 6813668,
+        "num_examples": 11144,
+        "dataset_name": "scat"
+      },
+      "validation": {
+        "name": "validation",
+        "num_bytes": 93178,
+        "num_examples": 144,
+        "dataset_name": "scat"
+      },
+      "test": {
+        "name": "test",
+        "num_bytes": 583831,
+        "num_examples": 973,
+        "dataset_name": "scat"
+      }
+    },
+    "download_checksums": {
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.train.context.en": {
+        "num_bytes": 2314611,
+        "checksum": "5b12687b8a1779f7ae9bb55bfd21c09bae8dd4f9fffb483aabaa4bab7971a843"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.train.en": {
+        "num_bytes": 873040,
+        "checksum": "d2e94f2ee4c44c572094a0b397685d1bd361d2d8c474aa1bbcca471f539b702a"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.train.context.fr": {
+        "num_bytes": 2482190,
+        "checksum": "65dfd761f5ce42a560a4a1e93a62a7d5286137d15a28c131e7326b108a710496"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.train.fr": {
+        "num_bytes": 964130,
+        "checksum": "9ddb502f989b2f99fd24e5db566dfd02ab40dabcb79129ecc58c7acc2bd5473a"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.valid.context.en": {
+        "num_bytes": 31100,
+        "checksum": "91454b2879699928e921eb44af718378de285ac80821daba22dc9ea083f3b732"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.valid.en": {
+        "num_bytes": 11363,
+        "checksum": "b27fadf69941502023d721c6c9542cd0b895624df8d9ffb7384030d6a7c10e39"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.valid.context.fr": {
+        "num_bytes": 35187,
+        "checksum": "973748c53f5e5e06e2f11ad6f231b711cfec31f3bec331281c6d8d15704256bf"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.valid.fr": {
+        "num_bytes": 13206,
+        "checksum": "cfc9c4de44495a5605f75b1265411f95c0d3dac57019a5084e143b0e7ab0f476"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.test.context.en": {
+        "num_bytes": 188509,
+        "checksum": "363e2e40c758b0a9e6de58f6876fbef230d0dd072fc412f08cd4f1b3209b409e"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.test.en": {
+        "num_bytes": 75226,
+        "checksum": "845bd73b5372e395df5e3d2654f2e20e137f373002cc2b40dfc54c93de173d60"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.test.context.fr": {
+        "num_bytes": 214331,
+        "checksum": "fd7ff210b8ca104a5c9ee01e758afb216fc4f773a6b991d8fb158f5b3938bf14"
+      },
+      "https://huggingface.co/datasets/inseq/scat/resolve/main/filtered_scat/filtered.test.fr": {
+        "num_bytes": 90075,
+        "checksum": "7589f6cb024413d5b1c388616ddc4450e5f2657d304757d7b8e3d0893aae7cfe"
+      }
+    },
+    "download_size": 7292968,
+    "dataset_size": 7490677,
+    "size_in_bytes": 14783645
+  }

scat.py

@@ -57,7 +57,6 @@ _LICENSE = "Unknown"
 class ScatConfig(datasets.BuilderConfig):
     def __init__(
         self,
-        data_type: str,
         source_language: str, 
         target_language: str,
         **kwargs