Triple
T20194499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thunder Shock |
E493046
|
entity |
| Predicate | secondaryEffectChance |
P39645
|
FINISHED |
| Object | 10% |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 10% | Statement: [Thunder Shock, secondaryEffectChance, 10%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryEffectChance Context triple: [Thunder Shock, secondaryEffectChance, 10%]
-
A.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
B.
possibleSideEffect
chosen
Indicates that one entity may occur as a side effect or unintended consequence of another entity or action.
-
C.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
D.
tierEffect
Indicates how belonging to a particular tier influences or modifies the outcome, behavior, or properties associated with that tier.
-
E.
secondBowlEffect
Indicates the phenomenon where consuming a second bowl of food leads to a different (often diminished or altered) effect compared to the first bowl.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad7ed548190a893110fa2ffb144 |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b14c9d8819095453d0504d9222f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:37 p.m.