Triple
T24088434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barrow Airport |
E596713
|
entity |
| Predicate | hasCityServedFormerName |
P75589
|
FINISHED |
| Object | Barrow, Alaska |
—
|
NE NERFINISHED |
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: Barrow, Alaska | Statement: [Barrow Airport, hasCityServedFormerName, Barrow, Alaska]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityServedFormerName Context triple: [Barrow Airport, hasCityServedFormerName, Barrow, Alaska]
-
A.
formerNameOfCityServed
chosen
Indicates that one name was previously used for a city that is (or was) served by a particular entity, before being replaced by its current name.
-
B.
hasCityServedSuccessor
Indicates that one city served by a service, role, or entity is the successor to another previously served city in that same context.
-
C.
formerCityName
Indicates that an entity was previously known by a different city name in the past.
-
D.
servedCity
Indicates that a service, route, or facility operates in, reaches, or is available to a particular city.
-
E.
alternativeCityServed
Indicates that one city functions as an alternative service location for another city, typically in contexts like transportation or logistics.
- 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_69e288c4638c81909bacc28a1e3d436b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dc2c58448190a6e1cf25ae228a2e |
completed | April 29, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 10:48 p.m.