Triple
T4939915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armenian Soviet Socialist Republic |
E110900
|
entity |
| Predicate | usedScriptForArmenian |
P56657
|
FINISHED |
| Object | Armenian 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: Armenian alphabet | Statement: [Armenian Soviet Socialist Republic, usedScriptForArmenian, Armenian alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedScriptForArmenian Context triple: [Armenian Soviet Socialist Republic, usedScriptForArmenian, Armenian alphabet]
-
A.
formerScript
Indicates that an entity previously served as the script or writing system for another entity, but is no longer used in that role.
-
B.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
-
C.
associatedLanguageScript
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
D.
scriptUsedForLanguage
chosen
Indicates that a particular writing script is employed to write or represent a given language.
-
E.
usedScriptureTranslation
Indicates that one entity employed or relied on a particular translation of scripture in its actions, works, or communications.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd708a3dcc81908b6628864fe0db0a |
completed | March 20, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69bd6c389b9881908ad7fb1c5393c1b1 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.