Triple
T15268924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Bavarian |
E364969
|
entity |
| Predicate | notUsuallyUsedFor |
P7974
|
FINISHED |
| Object | formal writing |
—
|
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: formal writing | Statement: [Southern Bavarian, notUsuallyUsedFor, formal writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notUsuallyUsedFor Context triple: [Southern Bavarian, notUsuallyUsedFor, formal writing]
-
A.
notTypicallyUsedFor
chosen
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
B.
notUsedAt
Indicates that a particular entity is not utilized, applied, or active at a specified location, time, or context.
-
C.
isSometimesUsedFor
Indicates that something serves a particular purpose or function on some occasions, but not consistently or exclusively.
-
D.
notTypically
Indicates that the referenced situation, behavior, or relationship does not usually or normally occur under standard or expected conditions.
-
E.
notAutomaticallyUsedBy
Indicates that something is not used by another entity in an automatic or default manner and instead requires explicit action or configuration to be used.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0094ca9ac8190a1f97a7b74c96cd5 |
completed | April 15, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69deca90739081909bd1b797cdb8af2b |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:14 a.m.