Triple
T24740598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuckahoe, New Jersey |
E618546
|
entity |
| Predicate | nearShoreDestination |
P157073
|
FINISHED |
| Object | Sea Isle City, New Jersey |
—
|
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: Sea Isle City, New Jersey | Statement: [Tuckahoe, New Jersey, nearShoreDestination, Sea Isle City, New Jersey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearShoreDestination Context triple: [Tuckahoe, New Jersey, nearShoreDestination, Sea Isle City, New Jersey]
-
A.
nearShoreDestination
chosen
Indicates that a destination is located close to a shoreline or coastal area.
-
B.
nearestSea
Indicates that one location is the closest sea to a given place compared to all other seas.
-
C.
nearbyStrait
Indicates that one entity is located close to or adjacent to a particular strait.
-
D.
stateOnNearestShore
Indicates that an entity is located on the shore that is geographically closest to another specified reference point or entity.
-
E.
hasNearbyHarbor
Indicates that one location has a harbor situated close to it in geographic proximity.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:05 a.m.