Triple
T12656684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ELT |
E302300
|
entity |
| Predicate | primaryScienceStrength |
P106038
|
FINISHED |
| Object | high angular resolution |
—
|
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: high angular resolution | Statement: [ELT, primaryScienceStrength, high angular resolution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryScienceStrength Context triple: [ELT, primaryScienceStrength, high angular resolution]
-
A.
primaryScience
Indicates that one entity serves as the main or principal scientific focus, discipline, or domain associated with another entity.
-
B.
primaryScienceUse
Indicates that something serves as the main or principal scientific purpose or application of an entity or resource.
-
C.
primaryScienceMode
Indicates that a particular configuration, operation, or setting is designated as the main or default mode used for conducting scientific activities or observations.
-
D.
primaryScienceBand
Indicates that one entity serves as the main or principal science band associated with another entity.
-
E.
primaryTrainingFocus
Indicates the main area or aspect that training is chiefly directed toward or concentrated on.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d96179c7648190a05a13991d62bebb |
completed | April 10, 2026, 8:45 p.m. |
Created at: April 9, 2026, 5:18 p.m.