update data loader

README.md

@@ -65,15 +65,116 @@ Boolean Question Answering, Choice of Plausible Alternatives, Words-in-Context,
 
 ### Data Instances
 
-[More Information Needed]
+#### KB-BoolQ
+An example of a data point looks as follows.
+```
+{'paragraph': '두아 리파(Dua Lipa, 1995년 8월 22일 ~ )는 잉글랜드의 싱어송라이터, 모델이다. BBC 사운드 오브 2016 명단에 노미닛되었다. 싱글 "Be the One"가 영국 싱글 차트 9위까지 오르는 등 성과를 보여주었다.',
+ 'question': '두아 리파는 영국인인가?',
+ 'label': 1}
+```
+
+#### KB-COPA
+An example of a data point looks as follows.
+```
+{'premise': '물을 오래 끓였다.',
+ 'question': '결과',
+ 'alternative_1': '물의 양이 늘어났다.',
+ 'alternative_2': '물의 양이 줄어들었다.',
+ 'label': 1}
+```
+
+#### KB-WiC
+An example of a data point looks as follows.
+```
+{'word': '양분',
+ 'context_1': '토양에 [양분]이 풍부하여 나무가 잘 자란다.	',
+ 'context_2': '태아는 모체로부터 [양분]과 산소를 공급받게 된다.',
+ 'label': 1}
+```
+
+#### KB-HellaSwag
+An example of a data point looks as follows.
+```
+{'context': '모자를 쓴 투수가 타자에게 온 힘을 다해 공을 던진다. 공이 타자에게 빠른 속도로 다가온다. 타자가 공을 배트로 친다. 배트에서 깡 소리가 난다. 공이 하늘 위로 날아간다.',
+ 'ending_1': '외야수가 떨어지는 공을 글러브로 잡는다.',
+ 'ending_2': '외야수가 공이 떨어질 위치에 자리를 잡는다.',
+ 'ending_3': '심판이 아웃을 외친다.',
+ 'ending_4': '외야수가 공을 따라 뛰기 시작한다.',
+ 'label': 3}
+```
+
+#### KB-SentiNeg
+An example of a data point looks as follows.
+```
+{'sentence': '택배사 정말 마음에 듬',
+ 'label': 1}
+```
 
 ### Data Fields
 
-[More Information Needed]
+### KB-BoolQ
++ `paragraph`: a `string` feature
++ `question`: a `string` feature
++ `label`: a classification label, with possible values `False`(0) and `True`(1)
+
+
+### KB-COPA
++ `premise`: a `string` feature
++ `question`: a `string` feature
++ `alternative_1`: a `string` feature
++ `alternative_2`: a `string` feature
++ `label`: an answer candidate label, with possible values `alternative_1`(0) and `alternative_2`(1)
+
+
+### KB-WiC
++ `target_word`: a `string` feature
++ `context_1`: a `string` feature
++ `context_2`: a `string` feature
++ `label`: a classification label, with possible values `False`(0) and `True`(1)
+
+### KB-HellaSwag
++ `target_word`: a `string` feature
++ `context_1`: a `string` feature
++ `context_2`: a `string` feature
++ `label`: a classification label, with possible values `False`(0) and `True`(1)
+
+### KB-SentiNeg
++ `sentence`: a `string` feature
++ `label`: a classification label, with possible values `Negative`(0) and `Positive`(1)
+
 
 ### Data Splits
 
-[More Information Needed]
+#### KB-BoolQ
+
++ train: 3,665
++ dev: 700
++ test: 1,404
+
+#### KB-COPA
+
++ train: 3,076
++ dev: 1,000
++ test: 1,000
+
+#### KB-WiC
+
++ train: 3,318
++ dev: 1,260
++ test: 1,260
+
+#### KB-HellaSwag
+
++ train: 3,665
++ dev: 700
++ test: 1,404
+
+#### KB-SentiNeg
+
++ train: 3,649
++ dev: 400
++ test: 397
++ test_originated: 397 (Corresponding training data where the test set is originated from.)
 
 ## Dataset Creation
 

kobest_v1.py

@@ -34,6 +34,7 @@ _DATA_URLS = {
         "train": _URL + "/v1.0/SentiNeg/train.tsv",
         "dev": _URL + "/v1.0/SentiNeg/dev.tsv",
         "test": _URL + "/v1.0/SentiNeg/test.tsv",
+        "test_originated": _URL + "/v1.0/SentiNeg/test.tsv",
     },
     "hellaswag": {
         "train": _URL + "/v1.0/HellaSwag/train.tsv",
@@ -69,26 +70,6 @@ class KoBESTConfig(datasets.BuilderConfig):
         self.url = url
 
 
-# class KoBESTConfig(datasets.BuilderConfig):
-#     """BuilderConfig for KoTEST."""
-#
-#     def __init__(
-#         self,
-#         features,
-#         data_url,
-#         file_map,
-#         url,
-#         **kwargs,
-#     ):
-#         """BuilderConfig for KoTEST."""
-#
-#         super(KoBESTConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-#         self.features = features
-#         self.data_url = data_url
-#         self.file_map = file_map
-#         self.url = url
-
-
 class KoBEST(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [
         KoBESTConfig(name=name, description=_DESCRIPTION, data_url=_DATA_URLS[name], citation=_CITATAION, url=_URL)
@@ -144,6 +125,16 @@ class KoBEST(datasets.GeneratorBasedBuilder):
         dev = dl_manager.download_and_extract(self.config.data_url["dev"])
         test = dl_manager.download_and_extract(self.config.data_url["test"])
 
+        if self.config.data_url.get("test_originated"):
+            test_originated = dl_manager.download_and_extract(self.config.data_url["test_originated"])
+
+            return [
+                datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train, "split": "train"}),
+                datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": dev, "split": "dev"}),
+                datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test, "split": "test"}),
+                datasets.SplitGenerator(name="test_originated", gen_kwargs={"filepath": test_originated, "split": "test_originated"}),
+            ]
+
         return [
             datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train, "split": "train"}),
             datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": dev, "split": "dev"}),
@@ -195,16 +186,6 @@ class KoBEST(datasets.GeneratorBasedBuilder):
             df = df.dropna()
             df = df[['context', 'choice1', 'choice2', 'choice3', 'choice4', 'label']]
 
-            # for id_, row in df.iterrows():
-            #     yield id_, {
-            #         "context": str(row["context"]),
-            #         "ending_1": str(row["choice1"]),
-            #         "ending_2": str(int(row["choice2"])),
-            #         "ending_3": str(int(row["choice3"])),
-            #         "ending_4": str(int(row["choice4"])),
-            #         "label": str(row["label"]),
-            #     }
-            #
             df = df.rename(columns={
                 'context': 'context',
                 'choice1': 'ending_1',
@@ -217,18 +198,21 @@ class KoBEST(datasets.GeneratorBasedBuilder):
         elif self.config.name == "sentineg":
             df = pd.read_csv(filepath, sep="\t")
             df = df.dropna()
-            df = df[['Text', 'Label']]
 
-            # for id_, row in df.iterrows():
-            #     yield id_, {
-            #         "sentence": str(row["Text"]),
-            #         "label": str(int(row["Label"])),
-            #     }
+            if split == "test_originated":
+                df = df[['Text_origin', 'Label_origin']]
 
-            df = df.rename(columns={
-                'Text': 'sentence',
-                'Label': 'label',
-            })
+                df = df.rename(columns={
+                    'Text_origin': 'sentence',
+                    'Label_origin': 'label',
+                })
+            else:
+                df = df[['Text', 'Label']]
+
+                df = df.rename(columns={
+                    'Text': 'sentence',
+                    'Label': 'label',
+                })
 
         else:
             raise NotImplementedError
@@ -239,8 +223,12 @@ class KoBEST(datasets.GeneratorBasedBuilder):
 
 
 if __name__ == "__main__":
-    for task in ['boolq', 'copa', 'wic', 'hellaswag', 'sentineg']:
-        dataset = datasets.load_dataset("kobest_v1.py", task, ignore_verifications=True)
-        print(dataset)
-        print(dataset['train']['label'])
+    dataset = datasets.load_dataset("kobest_v1.py", 'sentineg', ignore_verifications=True)
+    ds = dataset['test_originated']
+    print(ds)
+
+    # for task in ['boolq', 'copa', 'wic', 'hellaswag', 'sentineg']:
+    #     dataset = datasets.load_dataset("kobest_v1.py", task, ignore_verifications=True)
+    #     print(dataset)
+    #     print(dataset['train']['label'])