Triple
T18157032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monaco Heliport |
E434657
|
entity |
| Predicate | hasWaitingLounge |
P3382
|
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: [Monaco Heliport, hasWaitingLounge, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaitingLounge Context triple: [Monaco Heliport, hasWaitingLounge, yes]
-
A.
hasWaitingArea
chosen
Indicates that an entity provides or includes a designated space where people can wait before receiving a service or proceeding to another area.
-
B.
hasWaitingList
Indicates that there exists a queue or list of entities waiting for access to, or participation in, the referenced resource, service, or opportunity.
-
C.
hasLobby
Indicates that an entity includes or is equipped with a lobby area as part of its premises or structure.
-
D.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
E.
hasLoungeType
Indicates that an entity is associated with, or classified by, a particular type or category of lounge.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debf43348190a22f23a4bbfab433 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.