Triple
T38464591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fake Crash |
E912531
|
entity |
| Predicate | hasDoppelgangerOf |
P144124
|
FINISHED |
| Object | Crash Bandicoot |
—
|
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: Crash Bandicoot | Statement: [Fake Crash, hasDoppelgangerOf, Crash Bandicoot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDoppelgangerOf Context triple: [Fake Crash, hasDoppelgangerOf, Crash Bandicoot]
-
A.
hasDoppelganger
chosen
Indicates that an entity has a counterpart or double that closely resembles it, often in appearance, behavior, or role.
-
B.
hasDoppelgangerTheme
Indicates that something features or involves a doppelganger-related theme, such as doubles, look-alikes, or mirrored identities.
-
C.
hasFictionalAlterEgoOf
Indicates that one entity is the fictional alter ego, persona, or alternate identity of another entity.
-
D.
isFictionalTwinOf
Indicates that one entity is the imagined or fictional twin counterpart of another entity, typically within a narrative or creative context.
-
E.
hasArchitecturalTwin
Indicates that two entities share nearly identical architectural design, form, or structure, effectively making them architectural counterparts or duplicates.
- 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_69f76e861d8c81908559031dc66e3c15 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:31 p.m.