Triple
T15113706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riviera of New York |
E360979
|
entity |
| Predicate | denotesSetting |
P1957
|
FINISHED |
| Object | urban beachfront |
—
|
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: urban beachfront | Statement: [Riviera of New York, denotesSetting, urban beachfront]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: denotesSetting Context triple: [Riviera of New York, denotesSetting, urban beachfront]
-
A.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
-
B.
notableSetting
Indicates that a particular place or environment is especially significant or prominent as the context in which an entity is situated or occurs.
-
C.
usedAsSettingFor
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) takes place.
-
D.
setting
chosen
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
E.
standardSettingFor
Indicates that one entity establishes or defines the norms, criteria, or benchmarks that another entity is expected to follow or be measured against.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058d786c8190937c6819255c01bd |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:05 a.m.