Triple
T12310615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graziella |
E293466
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Graziela |
E980110
|
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: Graziela | Statement: [Graziella, hasVariant, Graziela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Graziela Context triple: [Graziella, hasVariant, Graziela]
-
A.
Graziella
Graziella is a feminine given name of Italian origin, often associated with grace and elegance.
-
B.
Zénaïde
Zénaïde is a feminine given name of French origin, notably borne by Zénaïde Bonaparte, a member of Napoleon Bonaparte’s family.
-
C.
Suzana
Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Graciela
chosen
Graciela is a feminine given name of Spanish origin, often considered a variant of Graziella and related to the concept of grace.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f02c0508190b10c0627cdaaba76 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63eefad508190be266c776525a7cc |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:53 p.m.