Triple
T2139282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wide Field Camera 3 |
E46723
|
entity |
| Predicate | primaryScienceUse |
P37042
|
FINISHED |
| Object | deep field imaging |
—
|
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: deep field imaging | Statement: [Wide Field Camera 3, primaryScienceUse, deep field imaging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryScienceUse Context triple: [Wide Field Camera 3, primaryScienceUse, deep field imaging]
-
A.
primaryScience
Indicates that one entity serves as the main or principal scientific focus, discipline, or domain associated with another entity.
-
B.
primaryScienceBand
Indicates that one entity serves as the main or principal science band associated with another entity.
-
C.
usedInEducationIn
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
D.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
E.
secondScience
Indicates that the subject is the second entity in a sequence or ranking specifically within a scientific context or domain.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbf74147c81908793c3694894f94a |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbd96a3b0819081efbfef975e1513 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf71edf08190add69022aabfd49d |
completed | March 7, 2026, 6:02 a.m. |
Created at: March 4, 2026, 7:44 p.m.