Triple
T27201795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wiener Neustadt East Airport |
E683753
|
entity |
| Predicate | hasGrassAreas |
P45219
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Wiener Neustadt East Airport, hasGrassAreas, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrassAreas Context triple: [Wiener Neustadt East Airport, hasGrassAreas, yes]
-
A.
hasGrassSeatingArea
Indicates that an entity includes or provides a seating area located on a grass surface.
-
B.
hasMeadow
Indicates that one entity possesses, contains, or includes a meadow as part of its area or composition.
-
C.
hasGreenSpaces
chosen
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
D.
isGreenSpaceFor
Indicates that one entity serves as a designated green or open space intended for use or benefit by another entity.
-
E.
hasPastoralArea
Indicates that one entity is assigned to, responsible for, or associated with a specific pastoral area or pastoral care region 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_69eefad1fd5c8190a4a46ea6afe58bfa |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 27, 2026, 9:36 a.m.