Triple
T35680800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coney Hall |
E1031002
|
entity |
| Predicate | hasAmenityStyle |
P183819
|
FINISHED |
| Object | village-like shopping parade |
—
|
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: village-like shopping parade | Statement: [Coney Hall, hasAmenityStyle, village-like shopping parade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmenityStyle Context triple: [Coney Hall, hasAmenityStyle, village-like shopping parade]
-
A.
hasTourismStyle
Indicates the type or style of tourism associated with or characteristic of a particular entity.
-
B.
hasAmenityAccessTo
Indicates that an entity has the right or ability to use or benefit from a specified amenity or facility.
-
C.
hasRegionalAmenity
Indicates that a region provides or contains a specific amenity or facility within its area.
-
D.
accommodationStyle
Indicates the manner or type of lodging or housing arrangement provided or used in a given context.
-
E.
hasSceneryStyle
Indicates a relationship where something is characterized by or associated with a particular style or type of scenery.
- F. None of above. chosen
Provenance (4 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_69f76e0bb6608190ad3a1880be54a17d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a34e80dc8190980d5b7b0b91341d |
completed | May 3, 2026, 7:34 p.m. |
Created at: May 3, 2026, 4:05 p.m.