Triple
T30963260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the White Eagle (Serbia) |
E788883
|
entity |
| Predicate | alphabetOfOriginalName |
P170848
|
FINISHED |
| Object | Cyrillic 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: Cyrillic script | Statement: [Order of the White Eagle (Serbia), alphabetOfOriginalName, Cyrillic script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alphabetOfOriginalName Context triple: [Order of the White Eagle (Serbia), alphabetOfOriginalName, Cyrillic script]
-
A.
hasOriginalNameOf
Indicates that one entity is the original or earlier name from which another entity’s current or later name is derived.
-
B.
previouslyUsedAlphabet
Indicates that an entity once employed a particular alphabet in the past, but no longer uses it as its current writing system.
-
C.
alphabeticPartRepresents
Indicates that the alphabetic portion of an identifier, code, or label stands for or denotes a particular concept, category, or entity.
-
D.
nameInLatinAlphabet
Indicates that an entity’s name is written or represented using the Latin alphabet.
-
E.
nameInOriginalLanguage
Indicates that an entity’s name is given in its original or native language form.
- F. None of above. chosen
Provenance (4 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_69f224c3a6b48190951add9b7b7f0271 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f695f9fe7c819084322bf6cdc70a13 |
completed | May 3, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f695385a2881908cc28ef97fffc867 |
completed | May 3, 2026, 12:22 a.m. |
Created at: April 29, 2026, 8:54 p.m.