Triple
T21745149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airlock Module |
E536766
|
entity |
| Predicate | crewCapacityContext |
P8587
|
FINISHED |
| Object | supports multiple astronauts during EVA preparation |
—
|
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: supports multiple astronauts during EVA preparation | Statement: [Airlock Module, crewCapacityContext, supports multiple astronauts during EVA preparation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewCapacityContext Context triple: [Airlock Module, crewCapacityContext, supports multiple astronauts during EVA preparation]
-
A.
hasCrewCapacity
chosen
Indicates that an entity is capable of accommodating a specified number of crew members.
-
B.
launcherCapacity
Indicates the maximum number or size of items that a launcher is designed to hold or deploy.
-
C.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
D.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
E.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
- 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a75352c8190bcd46759562ee251 |
completed | April 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:49 p.m.