Triple
T27223181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pine Beach, New Jersey |
E681335
|
entity |
| Predicate | locatedInUrbanRegion |
P12103
|
FINISHED |
| Object | Jersey Shore region |
—
|
NE NERFINISHED |
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: Jersey Shore region | Statement: [Pine Beach, New Jersey, locatedInUrbanRegion, Jersey Shore region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInUrbanRegion Context triple: [Pine Beach, New Jersey, locatedInUrbanRegion, Jersey Shore region]
-
A.
locatedInUrbanizationType
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
B.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
-
C.
withinUrbanArea
chosen
Indicates that one entity is located inside the spatial boundaries of an urban area associated with another entity.
-
D.
isUrbanizedAround
Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
-
E.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
- 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_69eefac9f64c8190a07490fe0c8b72a3 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69fe9b0276d48190b554fa22b043e6d8 |
completed | May 9, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69fe999692b081909921e1148d66f0ef |
completed | May 9, 2026, 2:19 a.m. |
Created at: April 27, 2026, 9:43 a.m.