QReCC dataset (conversations only)

requirements.txt

@@ -1,3 +1,3 @@
-datamaestro>=1.1.0
+datamaestro>=1.1.1
 ir_datasets
 attrs

src/datamaestro_text/config/com/github/apple/ml-qrecc.py

@@ -0,0 +1,37 @@
+# See documentation on https://datamaestro.readthedocs.io
+
+from pathlib import Path
+from datamaestro.definitions import datatasks, datatags, dataset
+from datamaestro.data.ml import Supervised
+from datamaestro.download.archive import zipdownloader
+from datamaestro.utils import HashCheck
+from datamaestro_text.data.conversation.qrecc import QReCCDataset
+
+
+@datatags("conversation", "context", "query")
+@datatasks("query rewriting")
+@zipdownloader(
+    "data",
+    "https://github.com/apple/ml-qrecc/raw/main/dataset/qrecc_data.zip",
+    checker=HashCheck("f88fcc7ef3678cd6312080389c8abd67"),
+)
+@dataset(
+    Supervised[QReCCDataset, None, QReCCDataset],
+    url="https://github.com/apple/ml-qrecc",
+    doi="https://doi.org/10.48550/arXiv.2010.04898",
+    id="",
+)
+def main(data: Path):
+    """Open-Domain Question Answering Goes Conversational via Question Rewriting
+
+    We introduce QReCC (Question Rewriting in Conversational Context), an
+    end-to-end open-domain question answering dataset comprising of 14K
+    conversations with 81K question-answer pairs. The goal of this dataset is to
+    provide a challenging benchmark for end-to-end conversational question
+    answering that includes the individual subtasks of question rewriting,
+    passage retrieval and reading comprehension
+    """
+    return {
+        "train": QReCCDataset(path=data / "qrecc_train.json"),
+        "test": QReCCDataset(path=data / "qrecc_test.json"),
+    }

src/datamaestro_text/data/conversation/qrecc.py

@@ -0,0 +1,101 @@
+from functools import cached_property
+from typing import Iterator, List, Optional
+from attr import define
+import json
+from datamaestro.data import File
+from datamaestro.record import Record
+
+from datamaestro_text.data.ir.base import (
+    IDItem,
+    SimpleTextItem,
+)
+
+
+from .base import (
+    AnswerDocumentURL,
+    AnswerEntry,
+    ConversationTree,
+    EntryType,
+    RetrievedEntry,
+    SimpleDecontextualizedItem,
+    SingleConversationTree,
+)
+from . import ConversationDataset
+
+
+@define(kw_only=True)
+class QReCCDatasetEntry:
+    """A query with past history"""
+
+    conversation_no: int
+    """Conversation ID"""
+
+    turn_no: int
+    """The turn in the conversation"""
+
+    conversation_source: str
+    """Conversation source"""
+
+    question: str
+    """The last issued query"""
+
+    rewrite: str
+    """Manually rewritten query"""
+
+    context: List[str]
+    """The list of queries asked by the user"""
+
+    answer: str
+    """The answer"""
+
+    answer_url: str
+    """The URL containing the answer"""
+
+
+class QReCCDataset(ConversationDataset, File):
+    def entries(self) -> Iterator[QReCCDatasetEntry]:
+        """Iterates over re-written query with their context"""
+        with self.path.open("rt") as fp:
+            data = json.load(fp)
+
+        data = [
+            QReCCDatasetEntry(**{key.lower(): value for key, value in entry.items()})
+            for entry in data
+        ]
+        return iter(data)
+
+    def __iter__(self) -> Iterator[ConversationTree]:
+        history: List[Record] = []
+        current_id: Optional[str] = None
+
+        for entry in self.entries():
+            # Creates a new conversation if needed
+            if entry.conversation_no != current_id:
+                if current_id is not None:
+                    history.reverse()
+                    yield SingleConversationTree(current_id, history)
+
+                current_id = entry.conversation_no
+                history = []
+
+            # Add to current
+            history.append(
+                Record(
+                    IDItem(f"{entry.conversation_no}#{entry.turn_no}"),
+                    SimpleTextItem(entry.question),
+                    AnswerDocumentURL(entry.answer_url),
+                    SimpleDecontextualizedItem(entry.rewrite),
+                    EntryType.USER_QUERY,
+                )
+            )
+
+            history.append(
+                Record(
+                    AnswerEntry(entry.answer),
+                    EntryType.SYSTEM_ANSWER,
+                )
+            )
+
+        # Yields the last one
+        history.reverse()
+        yield SingleConversationTree(current_id, history)