Triple
T147084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ritchey–Chrétien reflector |
E3352
|
entity |
| Predicate | canInclude |
P1393
|
FINISHED |
| Object | field flattener 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: field flattener optics | Statement: [Ritchey–Chrétien reflector, canInclude, field flattener optics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canInclude Context triple: [Ritchey–Chrétien reflector, canInclude, field flattener optics]
-
A.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
B.
canEnforce
Indicates that one entity has the authority or capability to compel compliance with rules, decisions, or obligations upon another entity.
-
C.
canAlsoBe
Indicates that something has an additional possible state, role, or classification beyond its primary one.
-
D.
canRefer
Indicates that one entity has the ability or permission to mention, point to, or direct attention to another entity.
-
E.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.