Triple
T26216789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian Soviet Socialist Republic |
E655651
|
entity |
| Predicate | usedScriptForGeorgian |
P16462
|
FINISHED |
| Object | Georgian script |
—
|
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: Georgian script | Statement: [Georgian Soviet Socialist Republic, usedScriptForGeorgian, Georgian script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedScriptForGeorgian Context triple: [Georgian Soviet Socialist Republic, usedScriptForGeorgian, Georgian script]
-
A.
usesScriptFor
Indicates that one entity employs or relies on a particular script or writing system for its representation, communication, or operation.
-
B.
nativeNameScript
Indicates the writing system or script in which an entity’s native name is expressed.
-
C.
associatedLanguageScript
chosen
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
D.
laterUsedScript
Indicates that one entity adopted or employed the script of another entity at a later point in time.
-
E.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
- 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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60d1b90a88190a77dcad664786c53 |
completed | May 2, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 8:54 p.m.