Triple
T36937378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kino der Toten |
E913654
|
entity |
| Predicate | specialEnemyType |
P15619
|
FINISHED |
| Object | Hellhounds |
—
|
NE NERFINISHED |
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: Hellhounds | Statement: [Kino der Toten, specialEnemyType, Hellhounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialEnemyType Context triple: [Kino der Toten, specialEnemyType, Hellhounds]
-
A.
enemyType
chosen
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
B.
primaryEnemy
Indicates that one entity is the main or most significant adversary or opponent of another entity.
-
C.
enemyTypeOpposed
Indicates that one type of enemy is defined as being in opposition or conflict with another enemy type.
-
D.
enemyCharacter
Indicates that one character is hostile or opposed to another, typically treating them as an adversary or foe.
-
E.
enemyCharacterIn
Indicates that a character is located within or present inside an enemy-controlled area, zone, or context.
- 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_69f76e8a6a5c81909c1febf32bf3fe23 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: May 3, 2026, 4:13 p.m.