Triple
T36482760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soyuz program (space station operations phase) |
E898860
|
entity |
| Predicate | crewCapacityTypical |
P1931
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Soyuz program (space station operations phase), crewCapacityTypical, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewCapacityTypical Context triple: [Soyuz program (space station operations phase), crewCapacityTypical, 3]
-
A.
aircraftTypicalSeatingCapacity
Indicates the usual number of passenger seats an aircraft is designed or configured to accommodate under normal operating conditions.
-
B.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
C.
typicalCapacity
chosen
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
D.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
E.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
- 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_69f76e5a0e088190a2b6706aeb41723c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.