Triple
T24767652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orient, New York |
E619628
|
entity |
| Predicate | hasWaterfrontScenery |
P90917
|
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: [Orient, New York, hasWaterfrontScenery, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterfrontScenery Context triple: [Orient, New York, hasWaterfrontScenery, true]
-
A.
hasWaterfrontView
chosen
Indicates that a property or location offers a direct view of a body of water from its premises.
-
B.
hasWaterfrontType
Indicates that an entity is associated with a specific type or category of waterfront (e.g., oceanfront, lakefront, riverfront).
-
C.
hasWaterfrontPark
Indicates that a place or area includes or is associated with a park located directly along a body of water.
-
D.
hasWaterfrontUse
Indicates that an entity is used, designated, or suitable for activities or purposes directly related to a waterfront or shoreline area.
-
E.
hasWaterfrontArea
Indicates that an entity possesses or includes an area directly adjacent to or bordering a body of water.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 4:28 a.m.