Triple
T17140838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvio |
E415956
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Sílvio |
E1252148
|
NE 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: Sílvio | Statement: [Silvio, hasSpellingVariant, Sílvio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sílvio Context triple: [Silvio, hasSpellingVariant, Sílvio]
-
A.
Sílvio
chosen
Sílvio is a masculine given name of Portuguese origin, commonly used in Portuguese-speaking countries.
-
B.
Sérgio
Sérgio is a Portuguese given name commonly used in Brazil and other Lusophone countries.
-
C.
Salvio Pacheco
Salvio Pacheco was a 19th-century Californio ranchero and landowner whose legacy includes the founding and namesake of the city of Pacheco, California.
-
D.
Fabrício
Fabrício is the given name of Fabrício Werdum, a Brazilian mixed martial artist and former UFC heavyweight champion.
-
E.
Rogério
Rogério is a Brazilian former professional footballer best known as a legendary São Paulo FC goalkeeper and prolific goal-scorer, later becoming a football manager.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d44a508190a3a149c3a64957f5 |
completed | April 18, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01482cd918819082d18b3cb76394cb |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:36 a.m.