Triple
T34254903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BoardWalk Deli |
E878848
|
entity |
| Predicate | hasOutdoorBoardwalkAccess |
P84779
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [BoardWalk Deli, hasOutdoorBoardwalkAccess, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOutdoorBoardwalkAccess Context triple: [BoardWalk Deli, hasOutdoorBoardwalkAccess, yes]
-
A.
hasBoardwalkInfrastructure
Indicates that there exists constructed boardwalk-related facilities or structures associated with the subject.
-
B.
hasOutfieldBoardwalk
Indicates that an outfield area includes or is equipped with a boardwalk structure.
-
C.
isScenicWalkway
Indicates that a path or route is designated as a walkway notable for its visually appealing or picturesque surroundings.
-
D.
hasWaterfrontAccessTo
Indicates that one entity is directly adjacent to and can physically access a particular body of water, such as a lake, river, or ocean.
-
E.
hasOutdoorSpaceType
chosen
Indicates the specific kind of outdoor area associated with an entity, such as a balcony, terrace, garden, or patio.
- 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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72ad38a208190b4bdc828297f86ad |
completed | May 3, 2026, 11 a.m. |
| PD | Predicate disambiguation | batch_69f72a0243988190a43b8ea22457cd30 |
completed | May 3, 2026, 10:57 a.m. |
Created at: May 1, 2026, 1:56 a.m.