Triple
T38553523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flin Flon Airport |
E925177
|
entity |
| Predicate | has apron type |
P39065
|
FINISHED |
| Object | paved |
—
|
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: paved | Statement: [Flin Flon Airport, has apron type, paved]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has apron type Context triple: [Flin Flon Airport, has apron type, paved]
-
A.
hasApronType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of apron.
-
B.
hasApron
Indicates that one entity possesses or is wearing an apron in relation to another context or entity.
-
C.
hasApronUse
Indicates that an entity uses or is intended to use an apron in a particular context or activity.
-
D.
hasMilitaryApron
Indicates that a location or facility includes a designated apron area specifically used for military aircraft operations.
-
E.
apronBowPositionIndicates
Indicates that the position of an apron’s bow conveys or encodes specific information or meaning about the wearer.
- 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_69f76eaeb69c8190b367df9330d6f6af |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd31a897481908d9d8571e51f524f |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f81cbc8190b4fd3bfc3106c1f3 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:32 p.m.