Triple
T27076828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Head Harbour (East Quoddy) Lighthouse |
E685484
|
entity |
| Predicate | hasLaterOptic |
P25118
|
FINISHED |
| Object | Fresnel lens |
—
|
NE NERFINISHED |
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: Fresnel lens | Statement: [Head Harbour (East Quoddy) Lighthouse, hasLaterOptic, Fresnel lens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaterOptic Context triple: [Head Harbour (East Quoddy) Lighthouse, hasLaterOptic, Fresnel lens]
-
A.
usesOpticsType
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
B.
hasOpticalElement
Indicates that one entity includes, contains, or is equipped with a specific optical element as a component or part.
-
C.
laterLensType
chosen
Indicates that one lens type occurs or is used at a later time than another lens type in a temporal sequence.
-
D.
hasRefractor
Indicates that an entity possesses or is equipped with a refractor component or device.
-
E.
hasLongFocalLength
Indicates that one entity possesses or is characterized by a focal length that is relatively long compared to a standard or reference.
- 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_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 27, 2026, 8:31 a.m.