Triple
T2458893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arecibo Observatory |
E54484
|
entity |
| Predicate | primaryMirrorType |
P8982
|
FINISHED |
| Object | fixed spherical dish |
—
|
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: fixed spherical dish | Statement: [Arecibo Observatory, primaryMirrorType, fixed spherical dish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryMirrorType Context triple: [Arecibo Observatory, primaryMirrorType, fixed spherical dish]
-
A.
primaryMirrorShape
chosen
Indicates that one entity has a primary mirror whose geometric shape or curvature type is specified by the other entity.
-
B.
mirrorType
Indicates that one entity is a specific kind or category of mirror in relation to another entity.
-
C.
primaryMirrorConfiguration
Indicates the specific structural and optical setup used for a system’s primary mirror.
-
D.
secondaryMirrorShape
Indicates that one entity specifies or defines the geometric shape of a secondary mirror associated with another entity.
-
E.
mirrorTechnology
Indicates a relationship where one technology closely reflects, imitates, or duplicates the functionality or design of another.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.