Triple
T34109939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyaung U Airport |
E874810
|
entity |
| Predicate | servesHistoricCity |
P195130
|
FINISHED |
| Object | Bagan |
—
|
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: Bagan | Statement: [Nyaung U Airport, servesHistoricCity, Bagan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesHistoricCity Context triple: [Nyaung U Airport, servesHistoricCity, Bagan]
-
A.
passesHistoricCity
Indicates that a route, path, or entity travels through or goes by a city recognized for its historical significance.
-
B.
servesHistoricTown
chosen
Indicates that a service, route, or facility provides access or support to a town recognized for its historical significance.
-
C.
isHistoricalCity
Indicates that a city has historical significance, typically due to its age, past events, or preserved heritage.
-
D.
hasHistoricCity
Indicates that an entity possesses, contains, or is associated with a city recognized for its historical significance.
-
E.
isFromCityWithHistoricArchitecture
Indicates that an entity originates from a city known for its historically significant or architecturally notable buildings and structures.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff84202eb081908ae21a54a4414d68 |
completed | May 9, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69ff833065e4819098579129d4ee17d3 |
completed | May 9, 2026, 6:55 p.m. |
Created at: May 1, 2026, 1:53 a.m.