Kimi K2 vs Sonar Pro
tree_0028 · GameFAQs
Timeline
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Round Context
GameFAQs
Dead by Daylight for PlayStation 4
In the history of the GameFAQs Character Battle tournaments, two specific winners are widely cited as anomalies because they are not traditional RPG or Action adventure protagonists. One is an inanimate geometric shape from a seminal 1980s puzzle game, and the other is a champion from a modern MOBA whose victory was driven by a massive external community rally. Identify these two unique winners. For each, determine the year of their tournament victory, the name of the opponent they defeated in the Grand Final, and the winner's share of the final vote (expressed as a percentage).
Answer length: 200-300 words.
Show hidden checklists
- Entity 1: L-Block (from Tetris)
- Entity 2: Draven (from League of Legends)
- First Winner Year: 2007
- First Winner Opponent: Cloud Strife
- First Winner Vote Percentage: Approximately 55.8% (or 55.76%)
- Second Winner Year: 2013
- Second Winner Opponent: Link (from The Legend of Zelda)
- Second Winner Vote Percentage: Approximately 52.9%
The question requires Deep Reasoning to identify the entities 'L-Block' and 'Draven' based solely on their descriptions (geometric shape, MOBA champion) without naming them. It then demands Wide Aggregation to retrieve specific historical data points (Year, Opponent, Vote %) from two separate contest years (2007 and 2013) within the GameFAQs archive.
Judgment
Agent A correctly identified both entities (L-Block and Draven), satisfying the core Deep Logic of the prompt. However, it contained factual errors regarding the specific details: it incorrectly stated L-Block defeated Link (it was Cloud Strife) and provided incorrect vote percentages for both matches. Agent B failed the Deep Logic by incorrectly identifying the second winner as 'Hogger' (who never won a Character Battle) and hallucinating a tournament in 2015. Because the winner (Agent A) had factual errors on sub-points, the score is capped at BETTER.
Kimi K2
Moonshot AI
Sonar Pro
Perplexity