Triple
T550678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hellboy |
E11831
|
entity |
| Predicate | enemyType |
P15619
|
FINISHED |
| Object | occult threats |
—
|
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: occult threats | Statement: [Hellboy, enemyType, occult threats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enemyType Context triple: [Hellboy, enemyType, occult threats]
-
A.
primaryEnemy
Indicates that one entity is the main or most significant adversary or opponent of another entity.
-
B.
targetsAsRacialEnemy
Indicates that one party identifies and treats another party as an enemy specifically on the basis of their race.
-
C.
attackType
Indicates the specific method, style, or category of attack used in an aggressive or hostile action between entities.
-
D.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
E.
opposingForce
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
- F. None of above. chosen
Provenance (4 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499030cf4819089b9163102255e49 |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a49858abd48190bd4b002a93e4a908 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.