Triple
T2334669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Ossetia |
E44281
|
entity |
| Predicate | usesScriptForOssetian |
P16462
|
FINISHED |
| Object | Cyrillic |
—
|
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: Cyrillic | Statement: [South Ossetia, usesScriptForOssetian, Cyrillic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesScriptForOssetian Context triple: [South Ossetia, usesScriptForOssetian, Cyrillic]
-
A.
associatedLanguageScript
chosen
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
B.
usesScriptDerivedFrom
Indicates that one entity employs a writing system that is historically or structurally derived from the script used by another entity.
-
C.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
-
D.
usedScriptureTranslation
Indicates that one entity employed or relied on a particular translation of scripture in its actions, works, or communications.
-
E.
hasLanguageOfScripture
Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:51 p.m.