Hugging Face's logo

Datasets:
p2chp2t
/
pace

Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
100K - 1M
ArXiv:
Tags:
benchmark
retrieval
reasoning
personalization
conflict-aware
Libraries:
Datasets
pandas
Polars
Dataset card Data Studio Files
xet
 Community
1
pace / README.md
p2chp2t's picture
p2chp2t
Update README.md
606fe84 verified
preview code
|
Raw
History Blame Contribute Delete
3.52 kB
metadata 
language:
  - en
pretty_name: PACE
task_categories:
  - question-answering
tags:
  - benchmark
  - retrieval
  - reasoning
  - personalization
  - conflict-aware
size_categories:
  - 100K<n<1M
configs:
  - config_name: queries
    data_files:
      - split: test
        path: data/queries.parquet
  - config_name: corpus
    data_files:
      - split: test
        path: data/corpus.parquet
  - config_name: profiles
    data_files:
      - split: test
        path: data/profiles.parquet

PACE 🏃‍♂️

Dataset Description

Dataset Summary

PACE (Personalized Assistants for Conflict Evaluation) 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.

Dataset Structure

PACE is organized into three configurations that together represent each user-specific case:

  • Queries contains the user requests to be evaluated, along with their feasibility labels, reference judgments, and gold evidence document IDs.
  • Corpus contains the atomic facts that form each user-specific knowledge base. It includes both gold evidence and distractor documents used for retrieval.
  • Profiles contains the structured user profiles used to construct each case, including user attributes and information about relevant related individuals.

Queries

Field Description
case_id Identifier of the user-specific case / KB
window_start Start of the temporal context window
ref_date Reference date for the case
window_end End of the temporal context window
query_id Query identifier within the case
situation_type Situation category (temporal, personal, or state)
label Feasibility status (conflict or non_conflict)
query User request
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

Field Description
case_id Identifier of the user-specific case / KB
window_start Start of the temporal context window
ref_date Reference date for the case
window_end End of the temporal context window
doc_id Document identifier
text Atomic fact text
situation_type Situation category associated with the source query
label Feasibility status associated with the source query
kind gold or distractor

Profiles

Field Description
case_id Identifier shared with the queries and corpus subsets
persona_id Persona identifier from the original profile
seed Short profile summary
spec Nested structured profile information
relationships Nested relationship information for relevant alters

Citation

Please cite our work if you find the resources in this repository useful:

will be included soon