diff --git a/chunked_pooling/chunked_eval_tasks.py b/chunked_pooling/chunked_eval_tasks.py
index 23dbcbf..7417fa7 100644
--- a/chunked_pooling/chunked_eval_tasks.py
+++ b/chunked_pooling/chunked_eval_tasks.py
@@ -454,3 +454,69 @@ def load_data(self, **kwargs):
             self.relevant_docs[split] = qrels
 
         self.data_loaded = True
+
+
+class TriviaQAChunked(AbsTaskChunkedRetrieval):
+
+    _EVAL_SPLIT = ["test"]
+
+    metadata = TaskMetadata(
+        name='TriviaQAChunked',
+        description=('Retrieval dataset derived from TriviaQA for chunked evaluation.'),
+        reference='https://nlp.cs.washington.edu/triviaqa',
+        dataset={
+            'path': 'mandarjoshi/trivia_qa',
+            'revision': '0f7faf33a3908546c6fd5b73a660e0f8ff173c2f',
+            'name': 'rc',
+        },
+        type='Retrieval',
+        category='s2p',
+        eval_splits=['test'],
+        eval_langs=['eng-Latn'],
+        main_score='ndcg_at_10',
+        date=None,
+        form=None,
+        domains=None,
+        task_subtypes=None,
+        license=None,
+        socioeconomic_status=None,
+        annotations_creators=None,
+        dialect=None,
+        text_creation=None,
+        bibtex_citation=None,
+        n_samples=None,
+        avg_character_length=None,
+    )
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    def load_data(self, **kwargs):
+        if self.data_loaded:
+            return
+        self.corpus = {}
+        self.queries = {}
+        self.relevant_docs = {}
+
+        data = datasets.load_dataset(**self.metadata_dict["dataset"])
+        for split in self._EVAL_SPLIT:
+            corpus = {}
+            queries = {}
+            relevant_docs = {}
+            for i, row in enumerate(data[split]):
+                if len(row['entity_pages']['wiki_context']) < 1:
+                    continue
+                queries[f'q{i}'] = row['question']
+                relevant_docs[f'q{i}'] = dict()
+                for j, (title, content) in enumerate(
+                    zip(
+                        row['entity_pages']['title'],
+                        row['entity_pages']['wiki_context'],
+                    )
+                ):
+                    corpus[f'c{i}-{j}'] = {'title': title, 'text': content}
+                    relevant_docs[f'q{i}'][f'c{i}-{j}'] = 1
+            self.corpus[split] = corpus
+            self.queries[split] = queries
+            self.relevant_docs[split] = relevant_docs
+        self.data_loaded = True