fix dataset

data/tweet_ner7/test.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9a16630c973358b2da01be7d6422b2d868d8f8e14c993a2778e2504bca1bcd9b
-size 2323993
+oid sha256:c81a0636e99f9389e2df5e5eb731965e714e2ace6f3b734ce7944f46a161d619
+size 2272370

data/tweet_ner7/train.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cfd66a08fcd3ba2809d991218859b01690bce54b92d54d2857dbb9e08cea331c
-size 3838692
+oid sha256:1319759f9b33741bd24b0c2ec990ca8798ed5592a156f76ee4a9ee5f0d94671d
+size 3751975

data/tweet_ner7/validation.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:631de556cf9a94aadc7dc496353780f5454c4dbac40e5bd9e4fd9d7802e55be6
-size 475586
+oid sha256:391d7aa9abec70be6693b4c9c0e821e5b1e1b9dc318aec03889fde9ac5c1e89d
+size 464937

data/tweet_topic/test.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:af403aac629588548484961e79539be3b6ec19f5ef90c3cf421a6b726cf33d5d
-size 477695
+oid sha256:fc9608ff97c872ed5770b6651cc9d1e7718575dafe8b486e7bb8468352209935
+size 464731

data/tweet_topic/train.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d4bd21f70d3a0b9e543ac36c9223d4e8e01d3a56a717ec991db94062537f34fb
-size 1323428
+oid sha256:1ba297de0531647cfa2e12634e6402a39bf20749539036cc435ea1713dd3c303
+size 1286581

data/tweet_topic/validation.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:101bbcaf17f25cadd00fed901b772cf46b0c3b97978259ef8d110c60dc1dfdfb
-size 165104
+oid sha256:6b3d0ea649e19a43970a8a6fe9841602bd924538f998ac3e9b87488582334d0b
+size 160549

process/unify_sp_symbol.py

@@ -27,7 +27,8 @@ for i in glob("data/tweet_ner7/*.jsonl"):
             d['text'] = d['text'].replace(t, t_new)
             d['text_tokenized'] = [y if y != t else t_new for y in d['text_tokenized']]
             for e in d['entities']:
-                e['']
+                e['entity'] = e['entity'].replace(t, t_new)
+                e['entity'] = e['entity'].replace("{{USERNAME}}", "@user").replace("{{URL}}", "{URL}")
 
     with open(i, "w") as f:
         f.write("\n".join([json.dumps(j) for j in data]))

super_tweeteval.py

@@ -2,7 +2,7 @@
 import json
 import datasets
 
-_VERSION = "0.1.44"
+_VERSION = "0.1.5"
 _SUPER_TWEETEVAL_CITATION = """TBA"""
 _SUPER_TWEETEVAL_DESCRIPTION = """TBA"""
 _TWEET_TOPIC_DESCRIPTION = """
@@ -309,6 +309,7 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
                 datasets.features.ClassLabel(names=names))
             features["text_tokenized"] = datasets.Sequence(
                 datasets.Value("string"))
+            features["entities"] = datasets.Sequence({"entity": datasets.Value("string"), "type": datasets.Value("string")})
         if self.config.name in ["tweet_intimacy", "tweet_similarity"]:
             features["gold_score"] = datasets.Value("float32")
         if self.config.name == "tempo_wic":
@@ -348,11 +349,9 @@ class SuperTweetEval(datasets.GeneratorBasedBuilder):
                 names=label_classes)
             features["text"] = datasets.Value("string")
         if self.config.name == "tweet_sentiment":
-            label_classes = ["strongly negative", "negative",
-                             "negative or neutral", "positive", "strongly positive"]
             features["text"] = datasets.Value("string")
             names = ['anger', 'anticipation', 'disgust', 'fear', 'joy',
-                      'love', 'optimism', 'pessimism', 'sadness', 'surprise', 'trust']
+                     'love', 'optimism', 'pessimism', 'sadness', 'surprise', 'trust']
             features["gold_label_list"] = datasets.Sequence(
                 datasets.features.ClassLabel(names=names))