Triple
T32350417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gibson L-5 |
E826577
|
entity |
| Predicate | alsoUsedInGenre |
P6829
|
FINISHED |
| Object | country |
—
|
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: country | Statement: [Gibson L-5, alsoUsedInGenre, country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoUsedInGenre Context triple: [Gibson L-5, alsoUsedInGenre, country]
-
A.
usedGenre
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
B.
alsoUsedIn
chosen
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
-
C.
coveredInGenre
Indicates that a work or item is associated with, categorized under, or treated within a particular genre.
-
D.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
E.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
- 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_69f34914dfc48190a390cd0720d9e86f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6be56d7908190a730ed6da60acffd |
completed | May 3, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:49 a.m.