Triple
T28865483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filey Lifeboat Station |
E728984
|
entity |
| Predicate | safetyActivities |
P169658
|
FINISHED |
| Object | community sea safety education |
—
|
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: community sea safety education | Statement: [Filey Lifeboat Station, safetyActivities, community sea safety education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyActivities Context triple: [Filey Lifeboat Station, safetyActivities, community sea safety education]
-
A.
safetyChallenge
Indicates that one entity presents or poses a safety-related test, risk, or concern to another entity.
-
B.
encouragesActivities
Indicates that one entity promotes, supports, or motivates another entity to engage in certain activities.
-
C.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
D.
safetyAdvice
Indicates that one entity provides guidance or recommendations to another entity about how to avoid danger or reduce risk in a particular context.
-
E.
safetyPoints
Indicates a relationship where an entity is assigned or associated with a measure of safety, typically quantified as points reflecting its safety level or performance.
- 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_69f031a01cbc8190ba87270bb6fe4639 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f68048391c8190abe6580678f8a9ef |
completed | May 2, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f7e116c819099aec724e9ef3763 |
completed | May 2, 2026, 10:49 p.m. |
Created at: April 28, 2026, 6:48 a.m.