Triple
T6311119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julijan |
E141502
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Juliano |
E135120
|
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: Juliano | Statement: [Julijan, hasRelatedName, Juliano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juliano Context triple: [Julijan, hasRelatedName, Juliano]
-
A.
Julio
Julio is the given name of Julio Antonio Mella, a prominent early 20th-century Cuban communist leader and co-founder of the Cuban Communist Party.
-
B.
Giuliano
chosen
Giuliano is an Italian given name, equivalent to Julian, commonly used for males in Italian-speaking regions.
-
C.
Julián
Julián is a given name of Latin origin, commonly used in Spanish-speaking countries as a variant of Julian.
-
D.
Lúcio
Lúcio is a Brazilian architect and urban planner best known as the principal designer of Brasília, the country’s modernist capital city.
-
E.
Lucio
Lucio is a roguish, witty gentleman in Shakespeare’s play "Measure for Measure," known for his bawdy humor, moral hypocrisy, and role as a comic commentator on the play’s themes of justice and corruption.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0649d1e048190a3fc7fbce9d2ee57 |
completed | March 22, 2026, 9:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e461e2ec8190af7198a03edb1ff7 |
completed | March 27, 2026, 1:58 a.m. |
Created at: March 22, 2026, 4:28 p.m.