Triple
T249528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Salonga, New York |
E5111
|
entity |
| Predicate | residentialCharacter |
P662
|
FINISHED |
| Object | suburban |
—
|
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: suburban | Statement: [Fort Salonga, New York, residentialCharacter, suburban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: residentialCharacter Context triple: [Fort Salonga, New York, residentialCharacter, suburban]
-
A.
zoningCharacter
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
B.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
C.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
-
D.
fictionalResidence
Indicates that one entity is the place where another entity lives or is based within a fictional or imaginary context.
-
E.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d3728f0819086214ccc2db2305a |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b665f8c8190aac6fcbba2a0eebb |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.