Triple
T3097836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuyvesant Town–Peter Cooper Village |
E64641
|
entity |
| Predicate | hasGreenSpaceArea |
P45219
|
FINISHED |
| Object | large proportion of site |
—
|
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: large proportion of site | Statement: [Stuyvesant Town–Peter Cooper Village, hasGreenSpaceArea, large proportion of site]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenSpaceArea Context triple: [Stuyvesant Town–Peter Cooper Village, hasGreenSpaceArea, large proportion of site]
-
A.
hasGreenSpaces
chosen
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
B.
hasNearbyGreenSpace
Indicates that an entity is located close to an area of green space, such as a park, garden, or natural vegetation.
-
C.
isGreenSpaceFor
Indicates that one entity serves as a designated green or open space intended for use or benefit by another entity.
-
D.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
-
E.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada23dde988190a1aca020685594f3 |
completed | March 8, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69ad9df06ed88190809f0683122caa5a |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:03 p.m.