Triple
T25455267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corps des Pages |
E637896
|
entity |
| Predicate | hadBoardingSystem |
P158538
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Corps des Pages, hadBoardingSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadBoardingSystem Context triple: [Corps des Pages, hadBoardingSystem, yes]
-
A.
hasBoardingType
Indicates the specific manner or method by which an entity is boarded or accessed (e.g., how passengers or items are taken on).
-
B.
passengerSystem
Indicates a relationship where an entity functions as or belongs to a passenger-related system (such as a transport or service system designed for passengers).
-
C.
isBoarding
Indicates that an entity is in the process of getting onto or entering a vehicle, vessel, or similar mode of transport.
-
D.
hasBoardingAreaFor
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
E.
hasOnboardSystems
Indicates that an entity is equipped with or contains specific onboard systems or subsystems.
- F. None of above. chosen
Provenance (4 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_69e75db7c5048190b8da9cd7eeedb610 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f725e4d08190b0304e45a417193b |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 2:04 p.m.