Triple
T14479762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulln an der Donau |
E359067
|
entity |
| Predicate | hasParkOrGardenType |
P52905
|
FINISHED |
| Object | riverside parks |
—
|
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: riverside parks | Statement: [Tulln an der Donau, hasParkOrGardenType, riverside parks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkOrGardenType Context triple: [Tulln an der Donau, hasParkOrGardenType, riverside parks]
-
A.
hasParkAndGardenRegister
Indicates that an entity is recorded in an official register of parks and gardens.
-
B.
hasParkAndGardenGrade
Indicates that an entity has been assigned a specific quality or rating level for its parks and gardens.
-
C.
hasTypeOfPark
chosen
Indicates that an entity is associated with or classified by a specific type or category of park.
-
D.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
-
E.
hasGardenType
Indicates that an entity possesses or is associated with a garden of a specified type.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924a576c819098351efabdb779b1 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.