Triple
T1541365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paranal Observatory |
E32872
|
entity |
| Predicate | telescopeCount |
P2520
|
FINISHED |
| Object | four 8.2-metre Unit Telescopes |
—
|
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: four 8.2-metre Unit Telescopes | Statement: [Paranal Observatory, telescopeCount, four 8.2-metre Unit Telescopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: telescopeCount Context triple: [Paranal Observatory, telescopeCount, four 8.2-metre Unit Telescopes]
-
A.
telescopeArrayMemberCount
chosen
Indicates the number of individual telescopes that are part of a given telescope array.
-
B.
telescopeType
Indicates the specific kind or category of telescope associated with an entity.
-
C.
telescopeUsed
Indicates that a particular telescope was employed or utilized to perform an observation or related activity.
-
D.
telescopeArrayMember
Indicates that an entity is a component telescope belonging to a larger telescope array system.
-
E.
observatoryType
Indicates the specific kind or category of observatory associated with an entity.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa95c1a2948190a2b98469afec1a7d |
completed | March 6, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69a907b2453c8190a41f6b88c8217d1e |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.