Datasets:

LAMDA-NeSy
/

ChinaTravel-Sandbox

license: cc-by-4.0
language:
  - zh
  - en
tags:
  - travel-planning
  - language-agents
  - benchmark
configs:
  - config_name: attractions
    data_files:
      - split: zh
        path: data/zh/attractions.parquet
      - split: en
        path: data/en/attractions.parquet
  - config_name: restaurants
    data_files:
      - split: zh
        path: data/zh/restaurants.parquet
      - split: en
        path: data/en/restaurants.parquet
  - config_name: accommodations
    data_files:
      - split: zh
        path: data/zh/accommodations.parquet
      - split: en
        path: data/en/accommodations.parquet
  - config_name: trains
    data_files:
      - split: zh
        path: data/zh/trains.parquet
      - split: en
        path: data/en/trains.parquet
  - config_name: flights
    data_files:
      - split: zh
        path: data/zh/flights.parquet
      - split: en
        path: data/en/flights.parquet
  - config_name: poi
    data_files:
      - split: zh
        path: data/zh/poi.parquet
      - split: en
        path: data/en/poi.parquet
  - config_name: subway_stations
    data_files:
      - split: zh
        path: data/zh/subway_stations.parquet
      - split: en
        path: data/en/subway_stations.parquet

ChinaTravel Sandbox Environment Database

This dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).

English | 简体中文

Release version: 2026.08.2

English

This dataset contains the bilingual static sandbox used by ChinaTravel. It is a companion to the ChinaTravel query dataset and an artifact of the ChinaTravel paper.

The raw ZIP snapshots preserve the exact directory layout expected by the ChinaTravel evaluator. Viewer-friendly Parquet configs provide normalized tables for exploration and analysis. The raw snapshots remain the source of truth for benchmark execution.

Load normalized tables

from datasets import load_dataset

attractions_en = load_dataset(
    "LAMDA-NeSy/ChinaTravel-Sandbox",
    "attractions",
    split="en",
)
trains_zh = load_dataset(
    "LAMDA-NeSy/ChinaTravel-Sandbox",
    "trains",
    split="zh",
)

Table sizes

Config	Chinese rows	English rows
`attractions`	3413	3413
`restaurants`	4655	4655
`accommodations`	3866	3866
`trains`	5345	5345
`flights`	720	720
`poi`	12172	12172
`subway_stations`	3635	3635

Use with ChinaTravel

Download and extract one raw archive:

raw/ChinaTravel_sandbox_zh.zip contains database/.
raw/ChinaTravel_sandbox_en.zip contains database_en/.

Place the extracted directory under chinatravel/environment/. The English snapshot uses canonical concept labels. Its exact changes are documented in manifests/ENGLISH_FIXES.md and manifests/english_manifest.json.

Per-source-file checksums and a release manifest are included under manifests/ and at the repository root.

Data quality policy in 2026.08.2

The canonical Chinese executable cuisine value for the 66 corresponding Shanghai restaurant rows is 本帮菜; the English value remains Shanghai cuisine.
Natural-language queries may use varied expressions such as “上海菜”, “本帮菜”, or “上海特色美食”. Only executable DSL values are canonicalized.
The corrected 18:00 closing time for 富春山居号游船 / Fuchun Mountain Residence Cruise is retained.

Release 2026.08.1 briefly used 上海菜 as the Chinese executable value. The exact correction and validation boundary are documented in manifests/.

简体中文

本数据集包含 ChinaTravel 使用的中英文静态沙盒，是 ChinaTravel Query 数据集的配套资源，也是 ChinaTravel 论文的关联产物。

raw/ 中的 ZIP 保留测评代码所需的原始目录结构，是正式运行基准时的权威数据； Parquet config 用于 Hub viewer、检索和统计分析。

from datasets import load_dataset

restaurants_zh = load_dataset(
    "LAMDA-NeSy/ChinaTravel-Sandbox",
    "restaurants",
    split="zh",
)
poi_en = load_dataset(
    "LAMDA-NeSy/ChinaTravel-Sandbox",
    "poi",
    split="en",
)

解压中文包后得到 database/，解压英文包后得到 database_en/，将对应目录放到 chinatravel/environment/ 即可。英文版本已统一概念标签，具体修改和校验信息见 manifests/。

2026.08.2 将上海餐馆的中文可执行菜系规范值恢复为“本帮菜”，英文对应值仍为 Shanghai cuisine。自然语言 Query 可以继续使用“上海菜”“本帮菜”“上海特色美食” 等多样化表达，只有 DSL 和沙盒内部值需要统一。上一版已修复的富春山居号游船 18:00 闭馆时间保持不变，精确变更记录见 manifests/。

Citation

@inproceedings{shao2026chinatravel,
  title     = {ChinaTravel: An Open-Ended Travel Planning Benchmark with Compositional Constraint Validation for Language Agents},
  author    = {Jie-Jing Shao and Bo-Wen Zhang and Xiao-Wen Yang and Baizhi Chen and Siyu Han and Pang Jinghao and Wen-Da Wei and Guohao Cai and Zhenhua Dong and Lan-Zhe Guo and Yu-Feng Li},
  booktitle = {The Fourteenth International Conference on Learning Representations},
  year      = {2026},
  url       = {https://openreview.net/forum?id=0YRVlxY9BH}
}