Triple
T17069383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Portland dome diner |
E414172
|
entity |
| Predicate | travelClassServed |
P35839
|
FINISHED |
| Object | coach passengers |
—
|
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: coach passengers | Statement: [City of Portland dome diner, travelClassServed, coach passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelClassServed Context triple: [City of Portland dome diner, travelClassServed, coach passengers]
-
A.
travelClassRelevance
Indicates the degree to which a particular travel class (e.g., economy, business) is pertinent or applicable within a given travel context or scenario.
-
B.
servesTravelersTo
Indicates a relationship where one entity provides services, assistance, or accommodations specifically directed toward travelers heading to a particular destination.
-
C.
servesBusinessTravel
Indicates that an entity provides services or accommodations specifically intended for business-related travel.
-
D.
offersClassOfTravel
chosen
Indicates that a service provider makes a particular class or tier of travel (e.g., economy, business, first) available as an option.
-
E.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbbfb1f08190807301ff6e573cf5 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.