Triple
T13974892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juliana |
E336161
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Yuliana |
E343242
|
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: Yuliana | Statement: [Juliana, hasVariant, Yuliana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuliana Context triple: [Juliana, hasVariant, Yuliana]
-
A.
Yovanna
Yovanna is a fictional character played by actress Adria Arjona, known from her work in film and television.
-
B.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
C.
Romina
Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
-
D.
Julianna
chosen
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
E.
Fabiola
Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8fd6d48190a157eae8df3a2f3a |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd090350881909dd6ff12ec7e61dd |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:18 p.m.