Triple
T15387310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NTT |
E367947
|
entity |
| Predicate | hasCassegrainFocus |
P118581
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [NTT, hasCassegrainFocus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCassegrainFocus Context triple: [NTT, hasCassegrainFocus, yes]
-
A.
hasFocalRatio
Indicates a relationship where an optical system is associated with a specific focal ratio (f-number) that characterizes its light-gathering speed and image brightness.
-
B.
hasFocalPlane
Indicates that an optical system or imaging device possesses a specific focal plane where light is brought into focus.
-
C.
hasNumberOfNasmythFoci
Indicates the relationship specifying how many Nasmyth foci are associated with a given telescope or optical system.
-
D.
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.
-
E.
telescopeFocus
Indicates that one entity adjusts or sets the focal point of a telescope relative to another entity or target.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e761b688190893a81246b735b76 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:19 a.m.