Update README.md

README.md

@@ -28,22 +28,23 @@ configs:
       - split: test
         path: data/profiles.parquet
 ---
+
 # PACE 🏃‍♂️
-PACE (**P**ersonalized **A**ssistants for **C**onflict **E**valuation) is a benchmark for evaluating whether personalized assistants can identify situational conflicts between user requests and facts stored in a user-centric knowledge base.
 
 ## Dataset Description
 - **Repository:** [Code](https://github.com/p2chp2t/pacemaker)
 - **Paper:** [PACE: Towards Surfacing Hidden Conflicts in User Requests](link will be provided soon!)
 - **Point of Contact:** [Yoojin Kim](mailto:kimyujin1224@postech.ac.kr)
 
-## Data Structure
+## Dataset Summary
+PACE (**P**ersonalized **A**ssistants for **C**onflict **E**valuation) is a benchmark for evaluating whether personalized assistants can identify situational conflicts between user requests and facts stored in a user-centric knowledge base.
+PACE contains 3,249 queries across 185 user-specific cases, together with 376,448 atomic facts. Each query is labeled as either `conflict` or `non_conflict` and is associated with gold evidence from its corresponding knowledge base.
 
-The dataset is organized into three subsets:
-- **`queries`**: user requests, feasibility labels, rationales, and gold supporting document IDs.
-- **`corpus`**: atomic facts used as the retrieval corpus, including both gold and distractor documents.
-- **`profiles`**: structured user profiles associated with each case.
+## Dataset Structure
+The dataset is provided in three configurations: `queries`, `corpus`, and `profiles`. The `case_id` field links entries across the three configurations.
 
-### queries
+### `queries`
+Each row corresponds to a user request.
 | Field | Description |
 | --- | --- |
 | `case_id` | Identifier of the user-specific case / KB |
@@ -57,8 +58,8 @@ The dataset is organized into three subsets:
 | `context` | Context used during dataset construction |
 | `judgment` | Reference explanation for the feasibility decision |
 | `gold_doc_ids` | IDs of the gold corpus documents needed to resolve the query |
-
-### corpus
+### `corpus`
+Each row corresponds to an atomic fact in a user-specific knowledge base.
 | Field | Description |
 | --- | --- |
 | `case_id` | Identifier of the user-specific case / KB |
@@ -70,8 +71,8 @@ The dataset is organized into three subsets:
 | `situation_type` | Situation category associated with the source query |
 | `label` | Feasibility status associated with the source query |
 | `kind` | `gold` or `distractor` |
-
-### profiles
+### `profiles`
+Each row corresponds to a user profile.
 | Field | Description |
 | --- | --- |
 | `case_id` | Identifier shared with the `queries` and `corpus` subsets |
@@ -82,7 +83,6 @@ The dataset is organized into three subsets:
 
 
 ## Loading the Dataset
-
 ```python
 from datasets import load_dataset
 
@@ -105,10 +105,8 @@ profiles = load_dataset(
 )
 ```
 
-
 ## Citation
 Please cite our work if you find the resources in this repository useful:
-
 ```bibtex
 will be included soon
-```
+```