Lesson 1 discussed a fundamental question: why can prediction market prices be interpreted as probabilities. In Lesson 2, the issue becomes more specific and easier to overlook: when you see a market quote of 0.62, what exactly is the market pricing? Many participants focus entirely on the probability level without first verifying the event definition itself. As a result, they read the probability carefully but misunderstand the actual subject of the trade.
This is not a trivial issue. The most common mistakes in prediction markets don't necessarily come from incorrect directional judgment, but from "asking the wrong question." Under the same topic, two seemingly similar markets can end up with completely different settlement outcomes due to differences in deadlines, determination criteria, or data sources. Especially in macro and crypto events, a single word's boundary change in the text can decide whether the contract is triggered.
Therefore, the core of Lesson 2 is not about which side is more likely to occur, but first about reading the contract text clearly: what exactly are you betting on, who makes the determination, and when is it determined.
1. Three Elements of Event Contracts: Conditions, Timing, Source
Any prediction market contract must include at least three pieces of information to verify.
First, triggering conditions
What does it mean for an event to "occur"? Is it "price touches once" or "closes above"? Is it "official announcement" or "market consensus"? Is it "proposal passed" or "officially enacted"? If triggering conditions are unclear, all subsequent probability discussions will lose focus.
Second, time boundaries
What time window is the event valid within? For example, "before September 2026" and "in 2026" seem similar but are actually two different contracts. Time boundaries determine information value: the closer to the deadline, the more sensitive prices are to new information.
Third, settlement source
What source does the platform use to determine the outcome? Is it a government website, exchange announcement, official project blog, or a pre-agreed data provider? Settlement source is the anchor for dispute resolution and usually takes precedence over community consensus and media headlines.
Many users look at charts before rules; the correct order should be the opposite. Read the rules first, then check probabilities, and only then discuss positions.
2. Clear Events vs. Ambiguous Events: The Difficulty Isn't Equal
Not all prediction markets have the same information quality. Based on definition clarity, they can be roughly divided into two categories.
One type is clear events
Examples include sports results, election vote counts, or whether an official statistic meets a threshold. The determination source for these events is usually explicit, disputes are relatively rare in settlement, and prices are easier to interpret as "collective probability estimates for the same question."
The other type is ambiguous events
Examples include "whether a project succeeds," "whether a policy is favorable," or "whether a token enters mainstream." These descriptions are inherently vague—even if written as Yes/No markets, there may still be differences in interpretation. Ambiguous events tend to have high volume during periods of heightened sentiment but carry greater risks of dispute and misinterpretation.
For crypto topics, common ambiguities include: which metric to use for FDV, whether approval means submission passed or official enactment, and whether partnership refers to an MoU or commercial implementation. These may seem like wording details but can become core points of contention during settlement.
3. Why "High Price" Doesn't Equal "Clear Definition"
Some participants substitute volume or popularity for reading rules, assuming that "so many people trading means the question must be clearly defined." This is not reliable in practice.
High popularity may stem from interest in the event itself—it doesn't mean there's no ambiguity in the text. During hot periods, capital trades narratives first and checks terms later; but during settlement, it's the rule text that truly matters. An unintuitive reality in prediction markets is: the most hotly debated markets may also be those with the most misinterpretations.
Therefore, Lesson 2 offers a simple discipline: high popularity only means it's worth looking at; clear definition means it's worth reading; only when both are satisfied does probability have greater explanatory value.
4. Settlement Process: Automatic Settlement, Dispute Period, and Final Decision
Most platforms provide a broadly similar settlement process:
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After an event expires, result determination begins;
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If results are clear, the system settles automatically or semi-automatically according to rules;
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If disputes exist, a dispute resolution process begins;
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After disputes are resolved, final settlement occurs and funds are paid out.
There are two common misconceptions here. Misconception one: treating temporary displayed results as final results. Before disputes are closed, status on the interface may change. If participants treat intermediate states as final conclusions, they may form incorrect expectations.
Misconception two: treating external public opinion as the determination source. "Everyone knows the answer" on social platforms does not constitute settlement grounds. What's effective is the source and process specified in advance in the rules.
So in prediction markets, "who has the final say" isn't a moral issue—it's a contract issue. Before trading, you must know which mechanism holds ultimate decision-making power for this contract.
5. Reading in Gate Prediction Markets: Rules First, Probability Second
In Gate prediction market scenarios, users may access Polymarket-related markets with lower barriers by participating in event trading with spot USDT. This access method solves path friction but does not change the basic order of rule reading.
In practice, you can follow three steps:
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Read market details first. Confirm event conditions, deadline, settlement source, and dispute terms before checking prices.
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Then review probabilities and liquidity. Understand price as current consensus; don't treat any single quote as final judgment.
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Only then decide whether to participate. If your understanding of rules is incomplete, the safest move isn't to "try a small position," but not to participate yet.
In other words, Gate lowers operational complexity as an entry point, but contracts remain event contracts—reading obligations are not taken over by the platform.
6. Gate for AI Agent's Role in Prediction Market Trading: Assist Organization Without Replacing Determination
Gate for AI Agent's role should be limited to research side tasks—especially information and news organization. It can help summarize event timelines, capture relevant news articles, and quickly form lists of questions to be verified—but cannot replace checking market rules and official sources.
It can be used for:
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Organizing differences in descriptions of the same event across sources;
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Listing key time points and potential points of dispute;
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Aggregating relevant announcement links for manual review.
It cannot be used for:
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Letting Agents directly decide "this Yes definitely counts as occurred";
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Treating summary texts as final settlement grounds;
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Using natural language conclusions instead of original rule text.
This lesson suggests positioning Agents as research assistants—not arbiters. They're responsible for speeding up material collection—not for deciding contract meaning.
7. Lesson Summary
The core question of Lesson 2 is: how are events defined and settled? Prediction markets don't start with probability and fill in rules later; they start with rules—and only then probabilities become interpretable. Conditions, timing, and source determine what's being traded; settlement process and dispute mechanism determine final outcomes. If these aspects are ignored, even precise prices may be misread.
In combined scenarios involving Gate prediction markets and Gate for AI Agent, proper division of labor is: platform provides trading and information entry points; Agent assists with organizing clues; ultimate determination remains with rule text and specified sources. The next lesson will continue with a key question: once definitions are clear, how do you assess whether the market is "accurate"—which leads into calibration.
