Triple
T23080771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trasop |
E575462
|
entity |
| Predicate | hasTypeOfGreenAreaNearby |
P58534
|
FINISHED |
| Object | 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: parks | Statement: [Trasop, hasTypeOfGreenAreaNearby, parks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfGreenAreaNearby Context triple: [Trasop, hasTypeOfGreenAreaNearby, parks]
-
A.
hasNearbyGreenSpace
Indicates that an entity is located close to an area of green space, such as a park, garden, or natural vegetation.
-
B.
hasGreenSpaces
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
C.
isGreenSpaceFor
Indicates that one entity serves as a designated green or open space intended for use or benefit by another entity.
-
D.
isGreenSpaceType
chosen
Indicates that one entity is classified as a type or category of green space (such as parks, gardens, or natural vegetated areas) in relation to another.
-
E.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
- 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_69e245be28d48190ad1348d5a73db37d |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18c67e06881908d24d6267bb49553 |
completed | April 29, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:56 p.m.