Update tydiqa-goldp.py

tydiqa-goldp.py

@@ -28,44 +28,21 @@ the use of translation (unlike MLQA and XQuAD).
 
 _LANG = ["arabic", "bengali", "english", "finnish", "indonesian", "japanese", "korean", "russian", "swahili", "telugu", "thai"]
 
-_PRIMARY_URLS = "https://huggingface.co/datasets/khalidalt/tydiqa-goldp/resolve/main/primary_tasks/{split}/{language}-{split}.jsonl"
-_Secondary_URLS = "https://huggingface.co/datasets/khalidalt/tydiqa-goldp/resolve/main/{split}/{language}-{split}.jsonl"
-
+_URL = "https://huggingface.co/datasets/khalidalt/tydiqa-goldp/resolve/main/{split}/{language}-{split}.jsonl"
 _VERSION = datasets.Version("1.1.0", "")
 
 
 class tydiqa_GoldP(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [
-        TydiqaConfig(
-            name="primary_task",
-            description=textwrap.dedent(
-                """\
-          Passage selection task (SelectP): Given a list of the passages in the article, return either (a) the index of
-          the passage that answers the question or (b) NULL if no such passage exists.
-          Minimal answer span task (MinSpan): Given the full text of an article, return one of (a) the start and end
-          byte indices of the minimal span that completely answers the question; (b) YES or NO if the question requires
-          a yes/no answer and we can draw a conclusion from the passage; (c) NULL if it is not possible to produce a
-          minimal answer for this question."""
-            ),
-        ),
-        TydiqaConfig(
-            name="secondary_task",
-            description=textwrap.dedent(
-                """Gold passage task (GoldP): Given a passage that is guaranteed to contain the
-          answer, predict the single contiguous span of characters that answers the question. This is more similar to
-          existing reading comprehension datasets (as opposed to the information-seeking task outlined above).
-          This task is constructed with two goals in mind: (1) more directly comparing with prior work and (2) providing
-          a simplified way for researchers to use TyDi QA by providing compatibility with existing code for SQuAD 1.1,
-          XQuAD, and MLQA. Toward these goals, the gold passage task differs from the primary task in several ways:
-          only the gold answer passage is provided rather than the entire Wikipedia article;
-          unanswerable questions have been discarded, similar to MLQA and XQuAD;
-          we evaluate with the SQuAD 1.1 metrics like XQuAD; and
-         Thai and Japanese are removed since the lack of whitespace breaks some tools.
-          """
-            ),
+        datasets.BuilderConfig(
+            name=lang,
+            description=f"tydiqa-GoldP language {lang}",
+            version=_VERSION,
         )
         for lang in _LANG
     ]
+
+
     def _info(self):
         # TODO(tydiqa): Specifies the datasets.DatasetInfo object
 
@@ -108,7 +85,7 @@ class tydiqa_GoldP(datasets.GeneratorBasedBuilder):
         splits = {datasets.Split.TRAIN: "train", datasets.Split.VALIDATION: "dev"}
         
         data_urls = {
-            split: _Secondary_URLS.format(language=language, split=splits[split]) for split in splits
+            split: _URL.format(language=language, split=splits[split]) for split in splits
         }
         
         dl_paths = dl_manager.download(data_urls)