add other datasets

mrqa.py

@@ -95,6 +95,18 @@ class MRQA(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.1.0")
 
     BUILDER_CONFIGS = [
+        MRQAConfig(
+            name="searchqa",
+            data_url={"validation": _URLs["validation+SearchQA"],
+                      "train": _URLs["train+SearchQA"],
+                      "test": _URLs["validation+SearchQA"]}
+        ),
+        MRQAConfig(
+            name="squad",
+            data_url={"validation": _URLs["validation+SQuAD"],
+                      "train": _URLs["train+SQuAD"],
+                      "test": _URLs["validation+SQuAD"]}
+        ),
         MRQAConfig(
             name="newsqa",
             data_url={"validation": _URLs["validation+NewsQA"],
@@ -113,6 +125,12 @@ class MRQA(datasets.GeneratorBasedBuilder):
                       "train": _URLs["train+HotpotQA"],
                       "test": _URLs["validation+HotpotQA"]}
         ),
+        MRQAConfig(
+            name="triviaqa",
+            data_url={"validation": _URLs["validation+TriviaQA"],
+                      "train": _URLs["train+TriviaQA"],
+                      "test": _URLs["validation+TriviaQA"]}
+        ),
     ]
 
     def _info(self):
@@ -123,38 +141,9 @@ class MRQA(datasets.GeneratorBasedBuilder):
                 {
                     "subset": datasets.Value("string"),
                     "context": datasets.Value("string"),
-                    # "context_tokens": datasets.Sequence(
-                    #     {
-                    #         "tokens": datasets.Value("string"),
-                    #         "offsets": datasets.Value("int32"),
-                    #     }
-                    # ),
                     "qid": datasets.Value("string"),
                     "idx": datasets.Value("int32"),
                     "question": datasets.Value("string"),
-                    # "question_tokens": datasets.Sequence(
-                    #     {
-                    #         "tokens": datasets.Value("string"),
-                    #         "offsets": datasets.Value("int32"),
-                    #     }
-                    # ),
-                    # "detected_answers": datasets.Sequence(
-                    #     {
-                    #         "text": datasets.Value("string"),
-                    #         "char_spans": datasets.Sequence(
-                    #             {
-                    #                 "start": datasets.Value("int32"),
-                    #                 "end": datasets.Value("int32"),
-                    #             }
-                    #         ),
-                    #         "token_spans": datasets.Sequence(
-                    #             {
-                    #                 "start": datasets.Value("int32"),
-                    #                 "end": datasets.Value("int32"),
-                    #             }
-                    #         ),
-                    #     }
-                    # ),
                     "answers": datasets.Sequence(datasets.Value("string")),
                     "answer": datasets.Value("string"),
                 }
@@ -204,35 +193,19 @@ class MRQA(datasets.GeneratorBasedBuilder):
                 idx = 0
                 for row in f:
                     paragraph = json.loads(row)
-                    context = paragraph["context"].strip()
-                    if subset == "HotpotQA":
-                        context = context.replace("[PAR] ", "\n\n")
-                        context = context.replace("[TLE]", "Title:")
-                        context = context.replace("[SEP]", "\nPassage:").strip()
-                    # context_tokens = [{"tokens": t[0], "offsets": t[1]} for t in paragraph["context_tokens"]]
+                    context = clean_context(paragraph["context"])
                     for qa in paragraph["qas"]:
                         qid = qa["qid"]
                         question = qa["question"].strip()
-                        # question_tokens = [{"tokens": t[0], "offsets": t[1]} for t in qa["question_tokens"]]
-                        # detected_answers = []
-                        # for detect_ans in qa["detected_answers"]:
-                        #     detected_answers.append(
-                        #         {
-                        #             "text": detect_ans["text"].strip(),
-                        #             "char_spans": [{"start": t[0], "end": t[1]} for t in detect_ans["char_spans"]],
-                        #             "token_spans": [{"start": t[0], "end": t[1]} for t in detect_ans["token_spans"]],
-                        #         }
-                        #     )
-                        answers = qa["answers"]
+                        if question[-1] != "?":
+                            question += "?"
+                        answers = [clean_up_spaces(a) for a in qa["answers"]]
                         final_row = {
                             "subset": subset,
-                            "context": context,
-                            # "context_tokens": context_tokens,
+                            "context": clean_up_spaces(context),
                             "qid": qid,
                             "idx": idx,
-                            "question": question,
-                            # "question_tokens": question_tokens,
-                            # "detected_answers": detected_answers,
+                            "question": clean_up_spaces(question),
                             "answers": answers,
                             "answer": answers[0]
                         }
@@ -240,7 +213,53 @@ class MRQA(datasets.GeneratorBasedBuilder):
                         yield f"{source}_{qid}", final_row
 
 
+def clean_context(context):
+    return (
+        context.replace("[PAR] ", "\n\n")
+            .replace("[TLE]", "Title:")
+            .replace("[SEP]", "\nPassage:").strip()
+            .replace("<Li>", "")
+            .replace("</Li>", "")
+            .replace("<OI>", "")
+            .replace("</OI>", "")
+            .replace("<Ol>", "")
+            .replace("</Ol>", "")
+            .replace("<Dd>", "")
+            .replace("</Dd>", "")
+            .replace("<UI>", "")
+            .replace("</UI>", "")
+            .replace("<Ul>", "")
+            .replace("</Ul>", "")
+            .replace("<P>", "")
+            .replace("</P>", "")
+            .replace("[DOC]", "")
+    ).strip()
+
+
+def clean_up_spaces(s):
+    out_string = s
+    return (
+        out_string.replace(" .", ".")
+            .replace(" ?", "?")
+            .replace(" !", "!")
+            .replace(" ,", ",")
+            .replace(" ' ", "'")
+            .replace(" n't", "n't")
+            .replace(" 'm", "'m")
+            .replace(" 's", "'s")
+            .replace(" 've", "'ve")
+            .replace(" 're", "'re")
+            .replace("( ", "(")
+            .replace(" )", ")")
+            .replace(" %", "%")
+            .replace("`` ", "\"")
+            .replace(" ''", "\"")
+            .replace(" :", ":")
+    )
+
+
 if __name__ == '__main__':
     from datasets import load_dataset
-    ssfd_debug = load_dataset("mrqa.py", name="newsqa")
+
+    ssfd_debug = load_dataset("mrqa.py", name="squad")
     x = 5