Triple
T147089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ritchey–Chrétien reflector |
E3352
|
entity |
| Predicate | primaryUseEnvironment |
P853
|
FINISHED |
| Object | ground-based observatories |
—
|
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: ground-based observatories | Statement: [Ritchey–Chrétien reflector, primaryUseEnvironment, ground-based observatories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryUseEnvironment Context triple: [Ritchey–Chrétien reflector, primaryUseEnvironment, ground-based observatories]
-
A.
environmentType
chosen
Indicates the kind or category of environment associated with an entity or situation.
-
B.
primaryEcosystem
Indicates the main type of ecosystem in which an entity predominantly exists or operates.
-
C.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
-
D.
environmentalCondition
Indicates the state or characteristics of the surrounding physical environment that affect or describe a situation, process, or entity.
-
E.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
- 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.