Triple
T25905673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paraguayan peso |
E652743
|
entity |
| Predicate | symbolScript |
P161672
|
FINISHED |
| Object | Latin 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: Latin alphabet | Statement: [Paraguayan peso, symbolScript, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolScript Context triple: [Paraguayan peso, symbolScript, Latin alphabet]
-
A.
symbolText
Indicates that a symbol is associated with or represented by a specific piece of text.
-
B.
symbolNumber
Indicates a relationship where a specific numerical identifier is assigned to or associated with a particular symbol.
-
C.
symbolDerivation
Indicates a relationship where one symbol is derived, obtained, or formed from another symbol through some transformation or generative process.
-
D.
digitSymbols
Indicates a mapping between digits and the symbols used to represent those digits in a numeral system.
-
E.
draftSymbol
Indicates that one entity serves as a draft or provisional symbolic representation of another entity.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6200ac60481909895c61d050b1338 |
completed | May 2, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 22, 2026, 8:27 a.m.