Triple
T27712845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Killarney Lighthouse |
E698736
|
entity |
| Predicate | lightingPurpose |
P159141
|
FINISHED |
| Object | marine navigation safety |
—
|
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: marine navigation safety | Statement: [Killarney Lighthouse, lightingPurpose, marine navigation safety]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingPurpose Context triple: [Killarney Lighthouse, lightingPurpose, marine navigation safety]
-
A.
illuminationPurpose
chosen
Indicates that one entity serves the purpose of providing light or illumination for another entity or context.
-
B.
lightingRequirement
Indicates the level or type of light that is needed for something to function, grow, or be used properly.
-
C.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
D.
usesLightingFor
Indicates that one entity employs or relies on a particular lighting setup, technology, or condition to achieve a purpose or perform an action.
-
E.
lightingColor
Indicates the color or hue of the lighting applied to or associated with an entity.
- 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_69ef590f655c81909f93893b3b3219b2 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f635cdcff881908a30d6b18c2085f4 |
completed | May 2, 2026, 5:35 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 3:03 p.m.