Triple
T2977097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NuSTAR |
E80423
|
entity |
| Predicate | focalLengthExtensionMethod |
P44360
|
FINISHED |
| Object | deployable mast |
—
|
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: deployable mast | Statement: [NuSTAR, focalLengthExtensionMethod, deployable mast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focalLengthExtensionMethod Context triple: [NuSTAR, focalLengthExtensionMethod, deployable mast]
-
A.
telephotoOpticalZoom
Indicates that the relationship involves zooming in optically with a telephoto lens to magnify a subject without digital enlargement.
-
B.
cameraLensType
Indicates the specific type or category of lens used or associated with a camera.
-
C.
hasFocalRatioRange
Indicates that an entity is associated with a range of possible focal ratios, specifying the minimum and maximum f-number values it can have.
-
D.
hasFocalPlane
Indicates that an optical system or imaging device possesses a specific focal plane where light is brought into focus.
-
E.
lensCompressionFactor
Indicates the degree to which a lens alters perceived depth and distance relationships in an image compared to real-world geometry.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad998c589c8190b4530f3fb8975187 |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:58 p.m.