Datasets:

thinkwee
/

DDRBench_10K

table_name stringclasses 9 values	column_name stringlengths 3 22	comment stringlengths 9 58
companies	cik	Central Index Key - unique SEC identifier for each company
companies	entity_type	Type of business entity (e.g., Corporation, LLC)
companies	sic	Standard Industrial Classification code
companies	sic_description	Human-readable description of the SIC code
companies	name	Official company name
companies	ein	Employer Identification Number
companies	lei	Legal Entity Identifier
companies	description	Business description and operations summary
companies	website	Company website URL
companies	investor_website	Investor relations website URL
companies	category	Company category classification
companies	fiscal_year_end	End date of fiscal year (e.g., '12-31')
companies	state_of_incorporation	State where company is incorporated
companies	phone	Company phone number
companies	former_names	Previous company names (JSON array)
company_tickers	cik	Foreign key to companies table
company_tickers	ticker	Stock ticker symbol
company_tickers	exchange	Stock exchange where ticker is listed
company_addresses	cik	Foreign key to companies table
company_addresses	address_type	Type of address: 'mailing' or 'business'
company_addresses	street1	Primary street address
company_addresses	street2	Secondary street address
company_addresses	city	City name
company_addresses	state_or_country	State or country code
company_addresses	zip_code	Postal/ZIP code
company_addresses	country	Country name
company_addresses	country_code	ISO country code
financial_facts	cik	Foreign key to companies table
financial_facts	fact_name	Name of the financial metric (e.g., 'Assets', 'Revenues')
financial_facts	fact_value	Numeric value of the financial metric
financial_facts	unit	Unit of measurement (e.g., 'USD', 'shares')
financial_facts	fact_category	Category of financial data (us-gaap, ifrs-full, dei, etc.)
financial_facts	fiscal_year	Fiscal year of the data
financial_facts	fiscal_period	Fiscal period (FY, Q1, Q2, Q3, Q4)
financial_facts	end_date	End date of the reporting period
financial_facts	accession_number	SEC filing accession number
financial_facts	form_type	Type of SEC form (10-K, 10-Q, 8-K)
financial_facts	filed_date	Date the filing was submitted to SEC
financial_facts	frame	XBRL frame identifier
financial_facts	dimension_segment	Business segment dimension
financial_facts	dimension_geography	Geographic dimension
filings	cik	Foreign key to companies table
filings	accession_number	Unique SEC filing identifier
filings	filing_date	Date the filing was submitted
filings	report_date	End date of the reporting period
filings	form	Type of SEC form filed
filings	primary_document	Main document filename
filings	is_xbrl	Whether filing contains XBRL data
filings	is_inline_xbrl	Whether filing uses inline XBRL
filings	size	File size in bytes
table_comments	table_name	Name of the database table
table_comments	comment	Description of the table's purpose and contents
column_comments	table_name	Name of the database table
column_comments	column_name	Name of the column
column_comments	comment	Description of the column's purpose and contents
table_documentation	table_name	Name of the database table
table_documentation	documentation	Detailed technical documentation for the table
column_documentation	table_name	Name of the database table
column_documentation	column_name	Name of the column
column_documentation	documentation	Detailed technical documentation for the column

DDRBench: Deep Data Research Benchmark

📊 Leaderboard & Demo | 📄 Paper (Arxiv)

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:

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.