Baseline Versus Special Cases Sample Clauses

Baseline Versus Special Cases. Table 2 shows sensitivity and two comparisons to the baseline (Consensus) truth set: proportion of disagreement and proportion of reversed statements. Truth Set Sensitivity Disagreement Reversal Consensus 0.744 n/a n/a Union 0.782 0.064 0 Intersection 0.538 0.423 0.038 Judge A 0.769 0.051 0 Judge B 0.705 0.038 0 Judge C 0.756 0.115 0 Judge D 0.692 0.179 0 Table 2: Truth Set Comparisons Compared to the Random truth sets, there are greater differences in sensitivity and more varied levels of disagreement, ranging from a low of 3.8% for judge B to a high of 17.9% for judge D. The Intersection truth set was the only one where a significant difference in the baseline set was reversed. The 3.8% reversal rate represents three pairwise comparisons. All three include a single algorithm whose ranking dropped under the Intersection truth set. Figure 6 shows selected system F-scores under different truth sets. One notable outcome is that the system that is either first or tied for first in all other rankings performs relatively poorly in the Intersection truth set. As it turns out, that system has the highest recall of any tested, and presumably suffers the most under the stricter match criteria. A more detailed analysis of specific systems’ sensitivity (or lack thereof) in performance to different truth sets is a topic for future work. 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35 consensus union intersection judge A judge B judge C judge D 0.30 Figure 6: Selected System F Scores.
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Related to Baseline Versus Special Cases

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