Triple
T5333681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Observatoire de Nice |
E123371
|
entity |
| Predicate | largestTelescopeAperture |
P62889
|
FINISHED |
| Object | 76 cm |
—
|
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: 76 cm | Statement: [Observatoire de Nice, largestTelescopeAperture, 76 cm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestTelescopeAperture Context triple: [Observatoire de Nice, largestTelescopeAperture, 76 cm]
-
A.
wasWorldsLargestTelescope
Indicates that the subject telescope held the status of being the largest telescope in the world during a specified time period.
-
B.
primaryMirrorDiameter
Indicates the diameter of the primary mirror used in an optical system or instrument.
-
C.
auxiliaryTelescopeAperture
Indicates that one entity functions as the auxiliary telescope whose aperture (opening/diameter) is being specified or associated with another entity.
-
D.
telescopeApertureClass
Indicates the classification of a telescope based on the size or range of its aperture.
-
E.
twinTelescopeAperture
Indicates that two telescopes share the same aperture size or have apertures that are functionally equivalent.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85ac8e10819088b6a9e02d927044 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8501d53c81908371bd5195ba5703 |
completed | March 20, 2026, 5:33 p.m. |
Created at: March 20, 2026, 2 p.m.