Triple
T18410375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Püning |
E441740
|
entity |
| Predicate | writingSystemVariation |
P26603
|
FINISHED |
| Object | Latin alphabet |
—
|
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: Latin alphabet | Statement: [Püning, writingSystemVariation, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingSystemVariation Context triple: [Püning, writingSystemVariation, Latin alphabet]
-
A.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
B.
writingSystemUsedIn
chosen
Indicates that a particular writing system is employed for written communication within a given language, region, or context.
-
C.
writingSystemFeatures
Indicates the specific structural or functional characteristics that define how a particular writing system represents language.
-
D.
writingSystemStandardized
Indicates that a writing system has been formally codified and regulated according to an accepted standard or set of rules.
-
E.
writingSystemDevelopedFor
Indicates that a particular writing system was created or adapted specifically to be used for a given language, community, or purpose.
- 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5195df3288190be61f4053476c735 |
completed | April 19, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 10:47 a.m.