Triple
T21900470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Sirena |
E540793
|
entity |
| Predicate | hasHolographicCrew |
P77616
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [La Sirena, hasHolographicCrew, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHolographicCrew Context triple: [La Sirena, hasHolographicCrew, yes]
-
A.
hasExtendedCrew
Indicates that an entity is associated with an additional or supplementary group of crew members beyond its primary crew.
-
B.
C-32BHasFeature
Indicates that an entity (such as a product, system, or component) possesses or includes a specific feature identified as C-32B.
-
C.
hasOculus
Indicates that one entity possesses or is equipped with an oculus (a circular opening or eye-like feature).
-
D.
hasArtificialCrewmember
chosen
Indicates that an entity includes at least one crew member that is artificial (e.g., a robot or AI) rather than biological.
-
E.
intendedCrewVehicle
Indicates that a particular vehicle is designated or planned to be used by a specific crew.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fca2bf88190b2a5b912aa102513 |
completed | April 28, 2026, 8:59 p.m. |
| PD | Predicate disambiguation | batch_69e6be9a65888190a66598d62d20366c |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:07 p.m.