Triple
T20491586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RB-50 |
E502757
|
entity |
| Predicate | hasCrewFeature |
P140288
|
FINISHED |
| Object | pressurized crew compartments |
—
|
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: pressurized crew compartments | Statement: [RB-50, hasCrewFeature, pressurized crew compartments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrewFeature Context triple: [RB-50, hasCrewFeature, pressurized crew compartments]
-
A.
featureCrew
Indicates that a particular crew member is highlighted or designated as a featured participant within a crew-related context.
-
B.
hasCrewRole
Indicates that an entity serves in a specific role or position within a crew associated with another entity.
-
C.
hasCrewMember
Indicates that an entity includes or employs another entity as a member of its crew.
-
D.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
E.
refersToCrew
Indicates that one entity makes reference to, is associated with, or pertains to a specific crew or group of crew members.
- F. None of above. chosen
Provenance (4 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cba5b708190bef437acf6321b81 |
completed | April 20, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:35 a.m.