Triple
T12472429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue crew |
E298092
|
entity |
| Predicate | hasCrewRotationType |
P88726
|
FINISHED |
| Object | dual-crew system |
—
|
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: dual-crew system | Statement: [Blue crew, hasCrewRotationType, dual-crew system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrewRotationType Context triple: [Blue crew, hasCrewRotationType, dual-crew system]
-
A.
hasCrewReductionComparedTo
Indicates that one entity operates with a smaller crew size compared to another entity.
-
B.
isPermanentlyCrewed
Indicates that an object, such as a facility or vehicle, consistently has a crew present on a continuous, ongoing basis without planned periods of being uncrewed.
-
C.
hasArtificialCrewmember
Indicates that an entity includes at least one crew member that is artificial (e.g., a robot or AI) rather than biological.
-
D.
crewComplementType
chosen
Indicates the classification or category of a crew complement associated with an entity (such as its role, composition, or staffing type).
-
E.
crewType
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.