Triple
T26616835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Wendell Crumb |
E668083
|
entity |
| Predicate | hasAlternatePersonalityCount |
P108136
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [Kevin Wendell Crumb, hasAlternatePersonalityCount, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternatePersonalityCount Context triple: [Kevin Wendell Crumb, hasAlternatePersonalityCount, 24]
-
A.
hasDifferentPersonalityIn
Indicates that an entity exhibits a different personality or character traits within a specified context, setting, or situation.
-
B.
hasMainPersonality
Indicates that one entity possesses or is characterized by a primary or dominant personality associated with another entity.
-
C.
featuresNumberOfPersonalities
chosen
Indicates that an entity is characterized by or contains a specified number of distinct personalities.
-
D.
hasFictionalAlterEgoOf
Indicates that one entity is the fictional alter ego, persona, or alternate identity of another entity.
-
E.
hasDoppelganger
Indicates that an entity has a counterpart or double that closely resembles it, often in appearance, behavior, or role.
- 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_69ee9cfe16088190a3dddd68e3c7b1ea |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 2:19 a.m.