Triple
T12196384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ghan |
E290594
|
entity |
| Predicate | hasLoungeCar |
P104264
|
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: [The Ghan, hasLoungeCar, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoungeCar Context triple: [The Ghan, hasLoungeCar, yes]
-
A.
hasLoungeType
Indicates that an entity is associated with, or classified by, a particular type or category of lounge.
-
B.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
C.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
D.
hasLoungeBrand
Indicates that an entity is associated with, or operates under, a particular lounge brand.
-
E.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d938ca32908190bd56f563efcbe8a0 |
completed | April 10, 2026, 5:52 p.m. |
Created at: April 8, 2026, 9:50 p.m.