Datasets:
File size: 3,512 Bytes
59cf266 264c020 59cf266 264c020 68b53eb 59cf266 264c020 59cf266 68b53eb 59cf266 69746de 59cf266 68b53eb 59cf266 68b53eb 59cf266 488f69e 68b53eb 107b7ed 59cf266 68b53eb 107b7ed 68b53eb 264c020 68b53eb 488f69e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 |
---
license: cc-by-sa-4.0
task_categories:
- table-question-answering
language:
- en
tags:
- finance
- 10k
- edgar
- agent
- benchmark
size_categories:
- 1M<n<10M
configs:
- config_name: column_documentation
data_files:
- split: train
path: data/column_documentation/column_documentation.parquet
- config_name: company_addresses
data_files:
- split: train
path: data/company_addresses/company_addresses.parquet
- config_name: column_comments
data_files:
- split: train
path: data/column_comments/column_comments.parquet
- config_name: sqlite_sequence
data_files:
- split: train
path: data/sqlite_sequence/sqlite_sequence.parquet
- config_name: table_documentation
data_files:
- split: train
path: data/table_documentation/table_documentation.parquet
- config_name: companies
data_files:
- split: train
path: data/companies/companies.parquet
- config_name: filings
data_files:
- split: train
path: data/filings/filings.parquet
- config_name: financial_facts
data_files:
- split: train
path: data/financial_facts/financial_facts.parquet
- config_name: company_tickers
data_files:
- split: train
path: data/company_tickers/company_tickers.parquet
- config_name: table_comments
data_files:
- split: train
path: data/table_comments/table_comments.parquet
---
# DDRBench: Deep Data Research Benchmark
[**📊 Leaderboard & Demo**](https://huggingface.co/spaces/thinkwee/DDR_Bench) | [**📄 Paper (Arxiv)**](https://arxiv.org/abs/2602.02039)
## Overview
**DDRBench (Deep Data Research Benchmark)** is a comprehensive evaluation framework designed to assess the capabilities of Large Language Model (LLM) agents in performing complex, multi-turn data research and reasoning tasks. Unlike traditional Q&A benchmarks, DDRBench focuses on scenarios requiring deep interaction with structured databases, tool usage, and long-context reasoning.
This dataset repository specifically hosts the **10-K Financial Database**, a core component of the DDRBench suite. It contains structured financial data extracted from SEC 10-K filings, enabling agents to answer intricate financial questions that mimic real-world analyst workflows.
## Dataset Structure
The dataset is organized into multiple configurations (subsets), representing different tables from the underlying SQLite database:
* **`financial_facts`**: The primary table containing over 5 million financial metrics (US-GAAP, IFRS) with values, units, and fiscal periods.
* **`companies`**: Registry of companies with CIK, names, and SIC codes.
* **`filings`**: Metadata for the SEC filings source documents.
* **`company_addresses`** & **`company_tickers`**: Geographic and market identification data.
* **`table_documentation`** & **`column_documentation`**: Meta-information describing the database schema to the agents.
## Usage
### Data Inspection
Load specific tables using the `datasets` library:
```python
from datasets import load_dataset
# Load the main financial facts table
financial_facts = load_dataset("thinkwee/DDRBench_10K", "financial_facts")
# Load company information
companies = load_dataset("thinkwee/DDRBench_10K", "companies")
```
For agent trajectories and evaluation logs, please refer to the [DDRBench Trajectory Dataset](https://huggingface.co/datasets/thinkwee/DDRBench_10K_trajectory).
### Run Deep Data Research
Please use the database file under ``/raw`` path and refer to https://github.com/thinkwee/DDR_Bench for running the agent.
|