Triple
T9890435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heavenly Palace |
E181436
|
entity |
| Predicate | maximumCrewDuringRotation |
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: [Heavenly Palace, maximumCrewDuringRotation, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumCrewDuringRotation Context triple: [Heavenly Palace, maximumCrewDuringRotation, 6]
-
A.
isPermanentlyCrewed
Indicates that an object, such as a facility or vehicle, consistently has a crew present on a continuous, ongoing basis without planned periods of being uncrewed.
-
B.
totalCrewMembers
Indicates the total number of crew members associated with a given entity or context.
-
C.
hasCrewCapacity
chosen
Indicates that an entity is capable of accommodating a specified number of crew members.
-
D.
honorsNumberOfPassengersAndCrew
Indicates that the subject recognizes or commemorates the specified count of passengers and crew.
-
E.
crewCount
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb47dfa908190884e96e5e5d6f41f |
completed | April 2, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69cd1d872d50819096b7ab166a8decf1 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:39 p.m.