Triple
T31516356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ironheart |
E804082
|
entity |
| Predicate | ageGroupOfAlterEgo |
P94896
|
FINISHED |
| Object | teenager |
—
|
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: teenager | Statement: [Ironheart, ageGroupOfAlterEgo, teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroupOfAlterEgo Context triple: [Ironheart, ageGroupOfAlterEgo, teenager]
-
A.
hasFictionalAlterEgoOf
Indicates that one entity is the fictional alter ego, persona, or alternate identity of another entity.
-
B.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
-
C.
hasAlterEgoCostume
Indicates that an entity has a distinct costume specifically associated with its alter ego identity.
-
D.
characterAgeDescriptor
chosen
Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
-
E.
ageVariants
Indicates that one entity is an alternative form or version of another distinguished specifically by age (e.g., younger/older or different life-stage variants).
- 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a25863648190867b5ad86681fee2 |
completed | May 3, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69f69fe82e5c81909da9db0a2f3bba6d |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:53 p.m.