Triple
T29555496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picton Airport |
E749892
|
entity |
| Predicate | usesForRecreation |
P80753
|
FINISHED |
| Object | recreational flying |
—
|
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: recreational flying | Statement: [Picton Airport, usesForRecreation, recreational flying]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesForRecreation Context triple: [Picton Airport, usesForRecreation, recreational flying]
-
A.
reconstructionUsedIn
Indicates that a particular reconstruction (e.g., a restored version or inferred structure) is employed or applied within a given context, process, or work.
-
B.
hasRecreationPurpose
chosen
Indicates that something is used or intended to be used for recreational or leisure activities.
-
C.
supportsRecreationAt
Indicates that one entity provides facilities, conditions, or resources that enable recreational activities to take place at a specified location.
-
D.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
E.
recreatedFor
Indicates that one entity has been created again or reproduced specifically for the benefit, use, or purpose of another entity.
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 28, 2026, 5:16 p.m.