Triple
T38634053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azelises |
E937531
|
entity |
| Predicate | writingSystemOnCoins |
P129388
|
FINISHED |
| Object | Greek 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: Greek alphabet | Statement: [Azelises, writingSystemOnCoins, Greek alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingSystemOnCoins Context triple: [Azelises, writingSystemOnCoins, Greek alphabet]
-
A.
writingSystemUsedOnCoins
chosen
Indicates that the coins feature inscriptions or markings written in the specified writing system.
-
B.
writingSystemUsedIn
Indicates that a particular writing system is employed for written communication within a given language, region, or context.
-
C.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
D.
writingSystemInspiredBy
Indicates that one writing system was developed based on, modeled after, or significantly influenced by another writing system.
-
E.
writingSystemDevelopedFor
Indicates that a particular writing system was created or adapted specifically to be used for a given language, community, or purpose.
- 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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:32 p.m.