Update tydiqa-goldp.py

tydiqa-goldp.py

@@ -36,15 +36,36 @@ _VERSION = datasets.Version("1.1.0", "")
 
 class tydiqa_GoldP(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name=lang,
-            description=f"tydiqa-GoldP language {lang}",
-            version=_VERSION,
-        )
+        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.
+          """
+            ),
+        ),
         for lang in _LANG
     ]
-
-
     def _info(self):
         # TODO(tydiqa): Specifies the datasets.DatasetInfo object