Triple
T12218884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chester Township, New Jersey |
E291157
|
entity |
| Predicate | hasOpenSpacePreservation |
P33583
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chester Township, New Jersey, hasOpenSpacePreservation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpenSpacePreservation Context triple: [Chester Township, New Jersey, hasOpenSpacePreservation, true]
-
A.
hasOpenSpacePreserve
Indicates that one entity possesses, contains, or is associated with an area designated as an open space preserve.
-
B.
hasConservationLand
chosen
Indicates that an entity possesses, manages, or is associated with land designated for environmental or natural resource conservation.
-
C.
hasGreenSpaces
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
D.
hasConservationFocusArea
Indicates that an entity is associated with a specific area or domain that is the focus of its conservation efforts or activities.
-
E.
hasConservationCommission
Indicates that an entity is associated with or overseen by a conservation commission.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.