Triple
T24551166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Haven Beach |
E607369
|
entity |
| Predicate | hasSafetyServiceNearby |
P124983
|
FINISHED |
| Object | RNLI presence in Little Haven |
—
|
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: RNLI presence in Little Haven | Statement: [Little Haven Beach, hasSafetyServiceNearby, RNLI presence in Little Haven]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyServiceNearby Context triple: [Little Haven Beach, hasSafetyServiceNearby, RNLI presence in Little Haven]
-
A.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
B.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
C.
hasNearbyInfrastructureType
chosen
Indicates that an entity is located close to infrastructure of a specified type.
-
D.
safetyResponse
Indicates how an entity reacts or what measures it takes in response to a potential or actual safety-related situation.
-
E.
hasOpenSpaceNearby
Indicates that an entity is located near or adjacent to an area that is open, unobstructed, or undeveloped.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8ccddec8190819e6366b3d6b6f0 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.