## Bar Charts: Distribution of Generated Sub-questions per Dataset (MetaQA) ### Overview The image contains three bar charts comparing the distribution of generated sub-questions across three datasets labeled "MetaQA 1-hop," "MetaQA 2-hop," and "MetaQA 3-hop." Each chart visualizes the frequency of datasets generating a specific number of sub-questions (0–6), with counts on the y-axis (0–80). ### Components/Axes - **X-axis**: "Number of Sub-questions" (categories: 0, 1, 2, 3, 4, 5, 6). - **Y-axis**: "Count" (linear scale, 0–80 in increments of 20). - **Legend**: No explicit legend is present. Each chart is labeled separately by hop count (1-hop, 2-hop, 3-hop). - **Bar Colors**: All bars are blue, with no differentiation between datasets within individual charts. ### Detailed Analysis #### MetaQA 1-hop - **Trend**: Dominated by a single bar at 1 sub-question (~80 count). - **Data Points**: - 0 sub-questions: 0 - 1 sub-question: ~80 - 2 sub-questions: ~5 - 3 sub-questions: ~3 - 4 sub-questions: ~2 - 5 sub-questions: ~1 - 6 sub-questions: ~1 #### MetaQA 2-hop - **Trend**: Peaks at 2 sub-questions (~85 count), with a secondary bar at 1 sub-question (~10 count). - **Data Points**: - 0 sub-questions: 0 - 1 sub-question: ~10 - 2 sub-questions: ~85 - 3 sub-questions: ~2 - 4 sub-questions: ~1 - 5 sub-questions: 0 - 6 sub-questions: 0 #### MetaQA 3-hop - **Trend**: Peaks at 3 sub-questions (~75 count), with a secondary bar at 2 sub-questions (~20 count). - **Data Points**: - 0 sub-questions: 0 - 1 sub-question: 0 - 2 sub-questions: ~20 - 3 sub-questions: ~75 - 4 sub-questions: ~3 - 5 sub-questions: 0 - 6 sub-questions: 0 ### Key Observations 1. **Peak Shift**: The optimal number of sub-questions increases with hop count (1 → 2 → 3). 2. **Decline in Frequency**: Counts drop sharply beyond the peak for each hop count. 3. **Sparsity**: Higher sub-question counts (4–6) are rare across all datasets. ### Interpretation The data suggests that the complexity of the task (measured by hop count) directly influences the number of sub-questions generated. For 1-hop tasks, most datasets generate a single sub-question, likely reflecting straightforward decomposition. As hop count increases, the model generates more sub-questions to handle multi-step reasoning, peaking at 2 for 2-hop and 3 for 3-hop. The sharp decline in counts for higher sub-question numbers implies that generating excessive sub-questions is either inefficient or unsupported by the dataset structure. This pattern aligns with expectations for hierarchical question decomposition, where deeper reasoning requires more granular sub-questions but remains bounded by practical limits.