Triple
T1677102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SUSAT sight |
E36254
|
entity |
| Predicate | objectiveLensDiameter |
P31648
|
FINISHED |
| Object | approximately 25 mm |
—
|
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: approximately 25 mm | Statement: [SUSAT sight, objectiveLensDiameter, approximately 25 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: objectiveLensDiameter Context triple: [SUSAT sight, objectiveLensDiameter, approximately 25 mm]
-
A.
laterLensType
Indicates that one lens type occurs or is used at a later time than another lens type in a temporal sequence.
-
B.
originalLens
Indicates that one lens is the initial or source lens from which another lens or lens configuration is derived or referenced.
-
C.
primaryMirrorDiameter
Indicates the diameter of the primary mirror used in an optical system or instrument.
-
D.
driverDiameter
Indicates the size of the circular cross-section of a driver component, typically measured as the distance across its widest point.
-
E.
cameraStyle
Indicates the characteristic visual approach or technique used by a camera in capturing or presenting imagery.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab272a653481908f48aa1eed5de8a4 |
completed | March 6, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69aa61b2f6288190b2348ef7d7e4672d |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab271be3f4819091adcd745dec8159 |
completed | March 6, 2026, 7:12 p.m. |
Created at: March 4, 2026, 7:29 p.m.