Triple
T36491761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omniglot |
E899066
|
entity |
| Predicate | backgroundSetUsedFor |
P15599
|
FINISHED |
| Object | meta-training |
—
|
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: meta-training | Statement: [Omniglot, backgroundSetUsedFor, meta-training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: backgroundSetUsedFor Context triple: [Omniglot, backgroundSetUsedFor, meta-training]
-
A.
hasBackground
Indicates that an entity possesses or is associated with a particular background, such as context, setting, or prior circumstances.
-
B.
usedAsSettingFor
chosen
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) takes place.
-
C.
usedCover
Indicates that one entity employed another entity as a protective or concealing cover in a given context.
-
D.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
-
E.
usedMask
Indicates that an entity has worn or utilized a particular mask.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.