Triple
T8417581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Out game |
E198764
|
entity |
| Predicate | typicalOpponentType |
P54987
|
FINISHED |
| Object | high-profile opponent |
—
|
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: high-profile opponent | Statement: [White Out game, typicalOpponentType, high-profile opponent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOpponentType Context triple: [White Out game, typicalOpponentType, high-profile opponent]
-
A.
featuresOpponentType
chosen
Indicates that an entity involves, includes, or is associated with an opponent of a specified type within a competitive or adversarial context.
-
B.
rivalOf
Indicates a relationship in which two entities compete against or oppose each other, often seeking advantage in the same domain or objective.
-
C.
opponentStrength
Indicates the level or degree of power, skill, or capability possessed by an opposing party in a competitive or adversarial context.
-
D.
keyOpponents
Indicates that the subject has primary or most significant opponents identified by the object.
-
E.
battleOpponent
Indicates that two entities are engaged in or designated as opponents in a battle or combat scenario.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb84c66b5c8190b9515f55dc08ac03 |
completed | March 31, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.