Triple
T4132719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Ubangi-Shari |
E85076
|
entity |
| Predicate | usedScriptInAdministration |
P45018
|
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: [French Ubangi-Shari, usedScriptInAdministration, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedScriptInAdministration Context triple: [French Ubangi-Shari, usedScriptInAdministration, Latin alphabet]
-
A.
scriptUsedCurrently
Indicates that a particular writing system or script is the one presently in use for a given language, text, or context.
-
B.
hasScriptUsage
chosen
Indicates that one entity uses, employs, or is written in the script or writing system specified by another entity.
-
C.
usesScriptDerivedFrom
Indicates that one entity employs a writing system that is historically or structurally derived from the script used by another entity.
-
D.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
-
E.
scriptUsedInSignage
Indicates that a particular writing system or script is employed in the text or graphics of a sign or signage.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:42 p.m.