Triple
T10939776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishopric of Hückeswagen |
E258436
|
entity |
| Predicate | primaryScriptForVernacular |
P6524
|
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: [Bishopric of Hückeswagen, primaryScriptForVernacular, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryScriptForVernacular Context triple: [Bishopric of Hückeswagen, primaryScriptForVernacular, Latin alphabet]
-
A.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
-
B.
associatedLanguageScript
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
C.
primaryScript
chosen
Indicates the writing system or script that is chiefly used to represent the language or content of an entity.
-
D.
nativeNameScript
Indicates the writing system or script in which an entity’s native name is expressed.
-
E.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c1389881909341170984211810 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.