Triple
T16237328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World’s End Reservation |
E394147
|
entity |
| Predicate | hasRecreationConstraint |
P122281
|
FINISHED |
| Object | no swimming in most areas |
—
|
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: no swimming in most areas | Statement: [World’s End Reservation, hasRecreationConstraint, no swimming in most areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecreationConstraint Context triple: [World’s End Reservation, hasRecreationConstraint, no swimming in most areas]
-
A.
hasRecreationType
Indicates that an entity is associated with or offers a particular type or category of recreational activity.
-
B.
hasRecreationSection
Indicates that an entity includes or is associated with a designated recreation section or recreational area.
-
C.
hasRecreationPurpose
Indicates that something is used or intended to be used for recreational or leisure activities.
-
D.
hasRecreationClassification
Indicates that an entity is assigned a specific type or category of recreational use or activity.
-
E.
hasRecreationContext
Indicates that an entity is associated with a recreational setting, purpose, or usage context.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2455bb23881909c4cb4c1439d2bc5 |
completed | April 17, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:04 a.m.