add reference columns to all splits

aes_enem_dataset.py

@@ -117,6 +117,7 @@ CSV_HEADERPROPOR = [
     "essay",
     "grades",
     "essay_year",
+    "reference"
 ]
 
 SOURCE_A_DESC = """
@@ -191,21 +192,34 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
     ]
 
     def _info(self):
-        features = datasets.Features(
-            {
-                "id": datasets.Value("string"),
-                "id_prompt": datasets.Value("string"),
-                "prompt": datasets.Value("string"),
-                "supporting_text": datasets.Value("string"),
-                "essay_title": datasets.Value("string"),
-                "essay_text": datasets.Value("string"),
-                "grades": datasets.Sequence(datasets.Value("int16")),
-                "essay_year": datasets.Value("int16"),
-                "general_comment": datasets.Value("string"),
-                "specific_comment": datasets.Value("string"),
-                "reference": datasets.Value("string"),
-            }
-        )
+        if self.config.name=="PROPOR2024":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "id_prompt": datasets.Value("string"),
+                    "essay_title": datasets.Value("string"),
+                    "essay_text": datasets.Value("string"),
+                    "grades": datasets.Sequence(datasets.Value("int16")),
+                    "essay_year": datasets.Value("int16"),
+                    "reference": datasets.Value("string"),
+                }
+            )
+        else:
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "id_prompt": datasets.Value("string"),
+                    "prompt": datasets.Value("string"),
+                    "supporting_text": datasets.Value("string"),
+                    "essay_title": datasets.Value("string"),
+                    "essay_text": datasets.Value("string"),
+                    "grades": datasets.Sequence(datasets.Value("int16")),
+                    "essay_year": datasets.Value("int16"),
+                    "general_comment": datasets.Value("string"),
+                    "specific_comment": datasets.Value("string"),
+                    "reference": datasets.Value("string"),
+                }
+            )
 
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
@@ -260,11 +274,42 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
         ]  # arbitrary removal of zero graded essays
         df.to_csv(filepath, index=False)
 
+    def _preprocess_propor2024(self, base_path: str):
+        for split_case in ["train.csv", "validation.csv", "test.csv"]:
+            filepath = f"{base_path}/propor2024/{split_case}"
+            df = pd.read_csv(filepath)
+    
+            # Dictionary to track how many times we've seen each (id, id_prompt) pair
+            counts = {}
+            # List to store the reference for each row
+            references = []
+    
+            # Define the mapping for each occurrence
+            occurrence_to_reference = {
+                0: "crawled_from_web",
+                1: "grader_a",
+                2: "grader_b"
+            }
+    
+            # Iterate through rows in the original order
+            for _, row in df.iterrows():
+                key = (row["id"], row["id_prompt"])
+                count = counts.get(key, 0)
+                # Assign the reference based on the count
+                ref = occurrence_to_reference.get(count, "unknown")
+                references.append(ref)
+                counts[key] = count + 1
+    
+            # Add the reference column without changing the order of rows
+            df["reference"] = references
+            df.to_csv(filepath, index=False)
+
     def _split_generators(self, dl_manager):
         urls = _URLS[self.config.name]
         extracted_files = dl_manager.download_and_extract({self.config.name: urls})
         if "PROPOR2024" == self.config.name:
             base_path = extracted_files["PROPOR2024"]
+            self._preprocess_propor2024(base_path)
             return [
                 datasets.SplitGenerator(
                     name=datasets.Split.TRAIN,
@@ -475,6 +520,7 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
                         "essay_text": row["essay"],
                         "grades": grades,
                         "essay_year": row["essay_year"],
+                        "reference": row["reference"]
                     }
         else:
             with open(filepath, encoding="utf-8") as csvfile: