added emoji data

data/tweet_emoji/map.txt

@@ -0,0 +1,100 @@
+0,😂
+1,😭
+2,❤
+3,🤣
+4,🔥
+5,🟩
+6,🥺
+7,🙏
+8,😍
+9,🥰
+10,🤔
+11,😩
+12,👍
+13,🙄
+14,😊
+15,💀
+16,👏
+17,✨
+18,😅
+19,👀
+20,💕
+21,😁
+22,💯
+23,🚀
+24,😔
+25,😘
+26,🔹
+27,💖
+28,😉
+29,💔
+30,🙌
+31,😎
+32,✅
+33,😳
+34,😆
+35,🥴
+36,🥲
+37,💗
+38,😌
+39,🤗
+40,👇
+41,🎉
+42,🙃
+43,☺
+44,🤡
+45,🤩
+46,🥳
+47,👌
+48,🙂
+49,😡
+50,😒
+51,😀
+52,😢
+53,🤦‍♂️
+54,😏
+55,🚨
+56,😬
+57,👉
+58,💪
+59,🎶
+60,😤
+61,😈
+62,😋
+63,🤪
+64,💞
+65,😫
+66,😄
+67,🤭
+68,🥹
+69,💰
+70,😃
+71,😜
+72,💥
+73,🤬
+74,😐
+75,✌
+76,🤤
+77,🙈
+78,🤨
+79,🌹
+80,😞
+81,🤧
+82,😹
+83,☹
+84,💓
+85,🥵
+86,😱
+87,💎
+88,💦
+89,🤮
+90,🤝
+91,🗣
+92,😇
+93,🤷‍♂️
+94,💋
+95,🤞
+96,🚩
+97,🤯
+98,🏆
+99,😑

super_tweet_eval.py

@@ -123,7 +123,16 @@ _TWEET_HATE_CITATION = """\
 }
 """
 _TWEET_DISAMBIGUATION_DESCRIPTION = """TBA"""
-_TWEET_DISAMBIGUATION_CITATION = """TBA"""
+_TWEET_DISAMBIGUATION_CITATION = """\
+@article{mishra2022tweetnerd,
+  title={TweetNERD--End to End Entity Linking Benchmark for Tweets},
+  author={Mishra, Shubhanshu and Saini, Aman and Makki, Raheleh and Mehta, Sneha and Haghighi, Aria and Mollahosseini, Ali},
+  journal={arXiv preprint arXiv:2210.08129},
+  year={2022}
+}
+"""
+_TWEET_EMOJI_DESCRIPTION = """TBA"""
+_TWEET_EMOJI_CITATION = """TBA"""
 
 
 class SuperTweetEvalConfig(datasets.BuilderConfig):
@@ -211,6 +220,13 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             citation=_TWEET_DISAMBIGUATION_CITATION,
             features=['gold_label_binary', 'target', 'context', 'definition', 'char_idx_start', 'car_idx_end'],
             data_url="https://huggingface.co/datasets/cardiffnlp/super_tweet_eval/resolve/main/data/tweet_disambiguation",
+        ),
+        SuperTweetEvalConfig(
+            name="tweet_emoji",
+            description=_TWEET_EMOJI_DESCRIPTION,
+            citation=_TWEET_EMOJI_CITATION,
+            features=['gold_label', 'text'],
+            data_url="https://huggingface.co/datasets/cardiffnlp/super_tweet_eval/resolve/main/data/tweet_emoji",
         )
     ]
 
@@ -251,6 +267,9 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
             features['char_idx_start'] = datasets.Value("int32")
             features['car_idx_end'] = datasets.Value("int32")
             features['gold_label_binary'] = datasets.Value("int32")
+        if self.config.name == "tweet_emoji":
+            features["gold_label"] = datasets.Value("int32")
+            features["text"] = datasets.Value("string")
 
         return datasets.DatasetInfo(
             description=_SUPER_TWEET_EVAL_DESCRIPTION + "\n" + self.config.description,