bugfix nerd + wic

super_tweet_eval.py

@@ -2,7 +2,7 @@
 import json
 import datasets
 
-_VERSION = "0.1.34"
+_VERSION = "0.1.35"
 _SUPER_TWEET_EVAL_CITATION = """TBA"""
 _SUPER_TWEET_EVAL_DESCRIPTION = """TBA"""
 _TWEET_TOPIC_DESCRIPTION = """
@@ -221,8 +221,8 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             description=_TEMPO_WIC_DESCRIPTION,
             citation=_TEMPO_WIC_CITATION,
             features=['gold_label_binary', 'word',
-                      'text_1', 'text_1_tokenized', 'token_idx_1', 'date_1',
-                      'text_2', 'text_2_tokenized', 'token_idx_2', 'date_2'],
+                      'text_1', 'text_1_tokenized', 'text_start_1', 'text_end_1',
+                      'text_2', 'text_2_tokenized', 'text_start_2', 'text_end_2'],
             data_url="https://huggingface.co/datasets/cardiffnlp/super_tweet_eval/resolve/main/data/tempo_wic",
         ),
         SuperTweetEvalConfig(
@@ -236,7 +236,7 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             name="tweet_nerd",
             description=_TWEET_NERD_DESCRIPTION,
             citation=_TWEET_NERD_CITATION,
-            features=['gold_label_binary', 'target', 'context', 'definition', 'char_idx_start', 'car_idx_end'],
+            features=['gold_label_binary', 'target', 'context', 'definition', 'text_start', 'text_end'],
             data_url="https://huggingface.co/datasets/cardiffnlp/super_tweet_eval/resolve/main/data/tweet_nerd",
         ),
         SuperTweetEvalConfig(
@@ -293,8 +293,8 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             features['target'] = datasets.Value("string")
             features['context'] = datasets.Value("string")
             features['definition'] = datasets.Value("string")
-            features['char_idx_start'] = datasets.Value("int32")
-            features['car_idx_end'] = datasets.Value("int32")
+            features['text_start'] = datasets.Value("int32")
+            features['text_end'] = datasets.Value("int32")
             features['gold_label_binary'] = datasets.Value("int32")
         if self.config.name == "tweet_emoji":
             features["gold_label"] = datasets.Value("int32")