Triple
T11311267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanford normal-incidence X-ray telescope experiments |
E267839
|
entity |
| Predicate | usedOpticsType |
P7239
|
FINISHED |
| Object | normal-incidence optics |
—
|
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: normal-incidence optics | Statement: [Stanford normal-incidence X-ray telescope experiments, usedOpticsType, normal-incidence optics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOpticsType Context triple: [Stanford normal-incidence X-ray telescope experiments, usedOpticsType, normal-incidence optics]
-
A.
usesOpticsType
chosen
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
B.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
-
C.
usesLensBrand
Indicates that one entity employs or operates using a lens produced by a specific brand.
-
D.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
E.
usesLaserType
Indicates that one entity employs or operates a specific type or category of laser in performing an action or function.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c1b7dc81908d8cc768c47390d3 |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.