data_id stringlengths 6 6 | domain stringclasses 5
values | image imagewidth (px) 821 2.07k | question stringlengths 110 312 | gold_answer stringlengths 1 266 | COT stringlengths 691 1.51k |
|---|---|---|---|---|---|
FIN-01 | Financial services | What is the difference between Unilever's and Colgate-Palmolive's market share in Apparel Care, and which brand's delta suggests it is closing the gap faster? | 11.9 percentage points; Unilever | To answer this question, let's break it down step by step:
1. Identify Unilever's market share in the Apparel Care category in Q3 FY2024: 21.3% with a delta of -0.7pp, with share erosion flagged.
2. Identify Colgate-Palmolive's market share in the Apparel Care category in Q3 FY2024: 9.4%.
3. Identify the delta values f... | |
FIN-02 | Financial services | Given the difference between the 1978 peak earnings yield of approximately 13.5% and the 1920 starting earnings yield of approximately 8.26%, and considering the 1920s to 1940s regime pattern of Expansion, Contraction, Contraction, is the 2020s Mixed regime more likely to transition to Expansion or Contraction? | Contraction | To answer this question, let's break it down step by step:
1. Identify the starting earnings yield in 1920 as shown on the earnings yield chart: 8.26
2. Identify the peak earnings yield in 1978: 13.5
3. Identify the decade regimes for the 1920s, 1930s, and 1940s as shown in chart c: The 1920s were Expansion, the 193... | |
GOV-01 | Government and policy | Is the 2023 unemployment rate lower or higher than the 1948 rate, and by how much does the 1983 peak exceed the 2023 rate? | lower; 7.4 percentage points | To answer this question, let's break it down step by step:
1. Identify the maximum unemployment rate during the Peak Unemployment Era from 1981 to 1985: 10.8
2. Identify the unemployment rate shown at the start of the chart in 1948: 3.8
3. Identify the unemployment rate at the end of the chart in 2023: 3.4
4. Determine... | |
EDU-01 | Education and edtech | What is the difference between the percentage of the number 1 and number 2 breakdown triggers for Powerschool? | 3.7 | To answer this question, let's break it down step by step:
1. Identify the top-ranked breakdown trigger for Powerschool in Panel 03 and its percentage value: The top-ranked breakdown trigger is Overlapping Category Labels, with a percentage value of 38.9%
2. Identify the second-ranked breakdown trigger for Powerschool ... | |
HLS-01 | Healthcare and life sciences | What is the difference between the SpO2 drop from h00 to h60 and the largest annotated point-to-point drop from 97% to 89%? | 7 | To answer this question, let's break it down step by step:
1. Identify the SpO2 value at h00: 96
2. Identify the SpO2 value at h60: 97
3. Identify the largest point-to-point drop in SpO2 noted on the chart from h60 to h66: 8 percentage points
4. Determine whether the change from h00 to h60 represents a drop and whether... | |
HLS-02 | Healthcare and life sciences | What is the spread between McDowell, WV's death rate and the Q5 Bin Lower Bound of 8.1 per 100K, who is the 5th highest Q5 county, and will the national average rate stay within or exceed the Q5 Floor by 2025? | 40.5; Pulaski, KY; within | To answer this question, let's break it down step by step:
1. Identify the death rate (deaths per 100K) for McDowell, WV as shown in the Q5 bin bar chart: 48
2. Identify the Q5 Bin Lower Bound value stated in the key metrics: 8.1
3. Determine the spread between McDowell, WV's death rate and the Q5 Bin Lower Bound: 48 -... | |
EDU-02 | Education and edtech | What is the ratio of Retail Business Intelligence Teams to Financial Services Analysts participants, and which cohort has the highest participant count overall? | 1.17; Retail Business Intelligence Teams | To answer this question, let's break it down step by step:
1. Identify the participant count for Retail Business Intelligence Teams: 2450
2. Identify the participant count for Financial Services Analysts: 2100
3. Review the participant counts for all five cohorts: Financial Services Analysts: 2100; Government Policy A... | |
SCI-01 | Scientific research and academia | Given that mBERT shows deep blue with very low similarity of approximately 30-35 on BoolQ O2-23 and blue on CoNLL O4-22, while ALBERT-xxlarge shows a near-white tone on BoolQ O2-23, does mBERT consistently show lower similarity than ALBERT-xxlarge, and what does this imply about mBERT's embeddings? | Yes, mBERT consistently shows lower cosine similarity than ALBERT-xxlarge on both BoolQ O2-23 with approximately 30-35 vs approximately 48-52 and CoNLL O4-22, implying mBERT produces more distinctive and spread-out embeddings, likely due to its multilingual training | To answer this question, let's break it down step by step:
1. The cosine similarity color pattern for mBERT on the BoolQ O2-23 benchmark is a deep blue tone, the darkest blue in the chart, indicating a very low cosine similarity score of approximately 30-35, the lowest in the entire heatmap.
2. The cosine similarity ... | |
FIN-03 | Financial services | Based on the descending pattern among South Asia ($1.1T), Latin America and the Caribbean ($0.9T), and Central and Eastern Europe ($0.8T), will Central and Eastern Europe's funding likely fall below $0.5T soon? | No | To answer this question, let's break it down step by step:
1. Identify the funding for South Asia: $1.1T
2. Identify the funding for Latin America and the Caribbean: $0.9T
3. Identify the funding for Central and Eastern Europe: $0.8T
4. Determine which region has the highest funding among the three: South Asia, with $1... | |
EDU-03 | Education and edtech | What is the difference between the peak borrower count in 2020 and the 2023 active borrower count, and does the OLS projection for 2025P show borrowers increasing or decreasing from 2023? | 2.1 M; decreasing | To answer this question, let's break it down step by step:
1. Identify the number of active borrowers in 2023: 43.2 M
2. Identify the peak borrower count and the year it occurred: 45.3 M in 2020
3. Determine whether the OLS projection for 2025P shows borrowers increasing or decreasing from 2023: increasing (however, th... | |
GOV-02 | Government and policy | In the Reclassification Rate chart, which theme has a higher rate between Rural-Urban Code greater than or equal to 7 and Socioeconomic T1, and by how many percentage points would the higher need to decrease to match the lower? | Rural-Urban Code ≥ 7; 5 percentage points | To answer this question, let's break it down step by step:
1. Identify the approximate reclassification rate for Rural-Urban Code greater than or equal to 7 in the Reclassification Rate by SVI Component Theme chart: 27
2. Identify the approximate reclassification rate for Socioeconomic T1 in the Reclassification Rate b... |
MM-Chart-QA
Read the blog post: Stop waiting for labeled data — generate evals
A multimodal chart-understanding dataset.
Schema
| Column | Type | Description |
|---|---|---|
data_id |
string | Presentable identifier of the form <DOMAIN>-<NN> (e.g. FIN-01, HLS-03). |
domain |
string | One of: Financial services, Healthcare and life sciences, Scientific research and academia, Government and policy, Education and edtech. |
image |
image | Chart image referenced by relative path under images/. |
question |
string | The chart-grounded question posed to the model. |
gold_answer |
string | Verifiable exact-match gold where possible; otherwise the original descriptive gold. |
COT |
string | Step-by-step chain-of-thought reasoning for the answer. |
Coverage
- Total domains supported: 5.
Usage
from datasets import load_dataset
ds = load_dataset("reinforcelabs/MM-Chart-QA")
ex = ds["test"][0]
print(ex["data_id"], ex["domain"])
print("Q:", ex["question"])
print("A:", ex["gold_answer"])
ex["image"].show()
Layout
.
├── README.md
├── data/
│ └── train-00000-of-00001.parquet
└── images/
├── FIN-01.png
├── FIN-02.png
└── ...
The parquet stores image references as {"bytes": <raw>, "path": "images/<data_id>.<ext>"}, and the image column carries {"_type": "Image"} metadata so datasets resolves it as a datasets.Image feature.
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