Triple
T27076827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Head Harbour (East Quoddy) Lighthouse |
E685484
|
entity |
| Predicate | hasOriginalOptic |
P134872
|
FINISHED |
| Object | catoptric lighting apparatus |
—
|
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: catoptric lighting apparatus | Statement: [Head Harbour (East Quoddy) Lighthouse, hasOriginalOptic, catoptric lighting apparatus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalOptic Context triple: [Head Harbour (East Quoddy) Lighthouse, hasOriginalOptic, catoptric lighting apparatus]
-
A.
originalLens
Indicates that one lens is the initial or source lens from which another lens or lens configuration is derived or referenced.
-
B.
usesOpticsType
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
C.
hasOpticalElement
chosen
Indicates that one entity includes, contains, or is equipped with a specific optical element as a component or part.
-
D.
hasMirrorOrLensMaterial
Indicates that an object’s mirror or lens component is made from a specified material.
-
E.
hasRefractor
Indicates that an entity possesses or is equipped with a refractor component or device.
- 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_69ef14843b1481909d828b3d5a44550a |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 27, 2026, 8:31 a.m.