Triple
T4637470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schmidt–Cassegrain telescope design |
E101567
|
entity |
| Predicate | correctsAberrationType |
P47350
|
FINISHED |
| Object | spherical aberration |
—
|
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: spherical aberration | Statement: [Schmidt–Cassegrain telescope design, correctsAberrationType, spherical aberration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correctsAberrationType Context triple: [Schmidt–Cassegrain telescope design, correctsAberrationType, spherical aberration]
-
A.
correctsAberration
chosen
Indicates that one entity counteracts, fixes, or compensates for an error, flaw, or deviation present in another entity.
-
B.
threatType
Indicates the specific category or nature of a threat that one entity poses or represents in relation to another.
-
C.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
-
D.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
E.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a62a9e48190b0cf1cbcc51f00c0 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.