Triple
T33320095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United BusinessFirst |
E853112
|
entity |
| Predicate | includedLoungeAccess |
P121590
|
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: [United BusinessFirst, includedLoungeAccess, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedLoungeAccess Context triple: [United BusinessFirst, includedLoungeAccess, yes]
-
A.
hasCustomerLounge
Indicates that an entity provides or includes a designated lounge area for customers to use.
-
B.
hasLoungeType
Indicates that an entity is associated with, or classified by, a particular type or category of lounge.
-
C.
hasLoungeBrand
Indicates that an entity is associated with, or operates under, a particular lounge brand.
-
D.
hasPassengerAmenity
chosen
Indicates that an entity provides or is equipped with a specific amenity intended for the comfort or convenience of its passengers.
-
E.
hasLoungeCar
Indicates that something includes or is equipped with a lounge car as part of its composition or configuration.
- 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0308a4591081909018e2ba5d70096e |
completed | May 12, 2026, 11:01 a.m. |
| PD | Predicate disambiguation | batch_6a03079299708190a2ecaf14d3f06f48 |
completed | May 12, 2026, 10:57 a.m. |
Created at: May 1, 2026, 1:33 a.m.