Triple
T37503152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nightmares |
E932022
|
entity |
| Predicate | usesEnemiesFrom |
P166898
|
FINISHED |
| Object | Zombies mode concepts |
—
|
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: Zombies mode concepts | Statement: [Nightmares, usesEnemiesFrom, Zombies mode concepts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesEnemiesFrom Context triple: [Nightmares, usesEnemiesFrom, Zombies mode concepts]
-
A.
usesEnemyFigure
chosen
Indicates that one entity employs or incorporates an enemy character or figure in relation to another entity or context.
-
B.
hasCommonEnemies
Indicates that two or more entities share at least one enemy in common.
-
C.
enemyCharacterIn
Indicates that a character is located within or present inside an enemy-controlled area, zone, or context.
-
D.
targetsAsRacialEnemy
Indicates that one party identifies and treats another party as an enemy specifically on the basis of their race.
-
E.
laterEnemyOf
Indicates that one entity becomes an enemy of another at a later time, after not initially being in an antagonistic relationship.
- 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_69f76ec5268481909ea01c73aeeefd42 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:17 p.m.