Triple
T1592794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiangong space station |
E34212
|
entity |
| Predicate | maximumCrewCapacity |
P8587
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Tiangong space station, maximumCrewCapacity, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumCrewCapacity Context triple: [Tiangong space station, maximumCrewCapacity, 6]
-
A.
hasCrewCapacity
chosen
Indicates that an entity is capable of accommodating a specified number of crew members.
-
B.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
C.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
D.
totalCrewMembers
Indicates the total number of crew members associated with a given entity or context.
-
E.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a916d413f08190a4e137e5ed262e25 |
completed | March 5, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69a907bfb39c8190a31e0be14d3d52e6 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.