Triple
T9917135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wentian |
E185896
|
entity |
| Predicate | crewCapacityRole |
P21064
|
FINISHED |
| Object | supports long-duration stays |
—
|
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 long-duration stays | Statement: [Wentian, crewCapacityRole, supports long-duration stays]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewCapacityRole Context triple: [Wentian, crewCapacityRole, supports long-duration stays]
-
A.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
B.
crewCount
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
-
C.
crewType
chosen
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
-
D.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
E.
crewRequired
Indicates that a certain number or type of crew members is necessary to operate or support the associated entity or activity.
- 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb540195881908f25f7dde5c66a75 |
completed | April 2, 2026, 12:16 a.m. |
| PD | Predicate disambiguation | batch_69cd1d90b8a8819081748f129c0c6ab6 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:42 p.m.