Triple
T26627636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VISTA Kilo-degree Infrared Galaxy survey |
E668399
|
entity |
| Predicate | telescopeFullName |
P161066
|
FINISHED |
| Object | Visible and Infrared Survey Telescope for Astronomy |
—
|
NE NERFINISHED |
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: Visible and Infrared Survey Telescope for Astronomy | Statement: [VISTA Kilo-degree Infrared Galaxy survey, telescopeFullName, Visible and Infrared Survey Telescope for Astronomy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: telescopeFullName Context triple: [VISTA Kilo-degree Infrared Galaxy survey, telescopeFullName, Visible and Infrared Survey Telescope for Astronomy]
-
A.
telescopeUnitName
Indicates the specific name assigned to a telescope unit within a larger telescope system or network.
-
B.
telescopeType
Indicates the specific kind or category of telescope associated with an entity.
-
C.
notableTelescope
Indicates that the subject is a telescope recognized for its significance, prominence, or special importance in some context.
-
D.
telescopeUsed
Indicates that a particular telescope was employed or utilized to perform an observation or related activity.
-
E.
observatoryName
Indicates the name assigned to an observatory.
- 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_69ee9cff507c819092b95bf7219a702e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f615ea59048190880a13cb9a9f8126 |
completed | May 2, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60f24ed608190bffe6c6084fc2f7a |
completed | May 2, 2026, 2:50 p.m. |
Created at: April 27, 2026, 2:23 a.m.