---
license: other
license_name: mixed-rights
license_link: https://github.com/wjh19990923/fred-sembench/blob/v1.0.0-paper/DATA_LICENSE.md
language:
  - en
pretty_name: FRED-SemBench
size_categories:
  - n<1K
task_categories:
  - question-answering
tags:
  - finance
  - macroeconomics
  - benchmark
  - agent-evaluation
  - semantic-reliability
configs:
  - config_name: questions
    data_files: questions.jsonl
  - config_name: facts
    data_files: facts.jsonl
  - config_name: llm_only_responses
    data_files: llm_only_responses.jsonl
  - config_name: fred_web_responses
    data_files: fred_web_responses.jsonl
  - config_name: iris_responses
    data_files: iris_responses.jsonl
  - config_name: llm_only_scores
    data_files: llm_only_scores.jsonl
  - config_name: fred_web_scores
    data_files: fred_web_scores.jsonl
  - config_name: iris_scores
    data_files: iris_scores.jsonl
  - config_name: llm_only_tool_traces
    data_files: llm_only_tool_traces.jsonl
  - config_name: fred_web_tool_traces
    data_files: fred_web_tool_traces.jsonl
  - config_name: iris_tool_traces
    data_files: iris_tool_traces.jsonl
  - config_name: iris_coverage_scores
    data_files: iris_coverage_scores.jsonl
  - config_name: iris_supported_questions
    data_files: iris_supported_questions.jsonl
  - config_name: source_provenance
    data_files: source_provenance.jsonl
---

# FRED-SemBench

[**Code & Evaluation (GitHub)**](https://github.com/wjh19990923/fred-sembench) | [**Paper (ACL Anthology)**](https://aclanthology.org/2026.finnlp-1.19/) | [**Paper-aligned Release**](https://github.com/wjh19990923/fred-sembench/releases/tag/v1.0.0-paper)

FRED-SemBench is a 200-question benchmark candidate for evaluating whether LLM
agents retrieve macroeconomic answers with the intended concept, series,
transformation, unit, observation period, and data-vintage semantics.

This dataset accompanies the FinNLP 2026 paper
[**“FRED-SemBench: Evaluating Semantic Reliability in LLM Access to
Macroeconomic Data”**](https://aclanthology.org/2026.finnlp-1.19/)
by Wilson Wang, Chandler Han, and Peter Zhang (Kairos-AI).

## Status and scope

- 50 independently selected macroeconomic concepts
- 100 verified derived fact records
- 200 machine-generated benchmark questions
- 48-question three-condition diagnostic evaluation
- 22-question pre-registered Iris-supported primary slice
- Full automated validation completed
- Independent domain adjudication remains future work

The dataset should therefore be treated as a paper-aligned benchmark candidate,
not as a fully adjudicated production benchmark.

## Quick start

```python
from datasets import load_dataset

questions = load_dataset(
    "wangjinh/FRED-SemBench",
    "questions",
    split="train",
)
```

## Configurations

The Hub viewer exposes separate configurations for questions, facts, each
condition's recorded responses, deterministic scores, credential-free tool
traces, and Iris coverage artifacts. Additional CSV/JSON metadata files are
available from **Files and versions**.

The evaluated conditions are:

1. `llm_only`: no external data tools;
2. `fred_web`: live Web search and a read-only FRED API wrapper;
3. `iris`: the Kairos-AI Iris semantic layer and CLI, with direct FRED, Web,
   and shell access disabled.

## Paper results

| Scope | LLM-only | FRED+Web | Iris |
| --- | ---: | ---: | ---: |
| Iris-supported slice | 4/22 | 13/22 | 17/22 |
| 48-question diagnostic slice | 4/48 | 28/48 | 25/48 |

The complete validation and reproduction code is available at:

<https://github.com/wjh19990923/fred-sembench>

The immutable paper-aligned artifact is available at:

<https://github.com/wjh19990923/fred-sembench/releases/tag/v1.0.0-paper>

## Data fields

`questions.jsonl` contains the natural-language question, concept and task
identifiers, explicit semantic gold contract, source attribution, precision,
scope expectations, confounders, and annotation status. See
`DATA_DICTIONARY.md` for the field-level description.

The response files contain the recorded final answer and operational metadata.
The score files contain deterministic classifications and component checks. The
trace files contain observable, allowlisted tool-call metadata and hashes, not
tool result bodies or hidden model reasoning.

## Privacy and commercial-system boundary

Per-run Codex thread identifiers were removed before publication. The release
does not contain API keys, authentication files, cookies, local runtime homes,
or hidden chain-of-thought.

Iris is a commercial Kairos-AI system. This release includes its paper prompts,
recorded responses, deterministic scores, coverage decisions, and
credential-free traces. It does not include the proprietary production
implementation or an entitlement to the commercial service.

## FRED source-data notice

Raw FRED CSV snapshots are intentionally not redistributed. The release retains
series identifiers, source URLs, retrieval dates, derived evidence, and
SHA-256 hashes for research auditability.

This product uses the FRED® API but is not endorsed or certified by the Federal
Reserve Bank of St. Louis. Individual series may carry source-specific
copyright and redistribution conditions. Users must comply with the current
FRED terms and each original provider's terms:

- <https://fred.stlouisfed.org/legal/>
- <https://fred.stlouisfed.org/docs/api/terms_of_use.html>

See `DATA_LICENSE.md` for the mixed-rights notice.

## Citation

Please cite the accompanying FinNLP 2026 paper, available on ACL Anthology:

<https://aclanthology.org/2026.finnlp-1.19/>

Citation files and evaluation code are maintained in the
[GitHub repository](https://github.com/wjh19990923/fred-sembench).

## Contact

Peter Zhang, corresponding author — founders@kairos-ai.io