Triple
T12286671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douai |
E292845
|
entity |
| Predicate | distanceToLens |
P104059
|
FINISHED |
| Object | about 25 km northeast |
—
|
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: about 25 km northeast | Statement: [Douai, distanceToLens, about 25 km northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLens Context triple: [Douai, distanceToLens, about 25 km northeast]
-
A.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
B.
tubeLengthRelativeToFocalLength
Indicates the relationship between an optical system’s tube length and its focal length, typically expressing how long the tube is relative to the focal length.
-
C.
minimumWorkingDistance
Indicates the shortest allowable distance that must be maintained between two entities for them to operate or interact safely or effectively.
-
D.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
-
E.
flangeFocalDistance
Indicates the distance between a lens mount’s flange surface and the image sensor or film plane where the image comes into focus.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d9261b7f088190b69fe6961015fce3 |
completed | April 10, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:52 p.m.