Triple
T10180887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laetitia |
E236777
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Letizia |
E369625
|
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: Letizia | Statement: [Laetitia, hasVariant, Letizia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Letizia Context triple: [Laetitia, hasVariant, Letizia]
-
A.
Letizia
chosen
Letizia is a feminine given name of Italian origin, famously borne by Maria Letizia Ramolino, the mother of Napoleon Bonaparte.
-
B.
Giuliana
Giuliana is an Italian feminine given name, commonly considered the female form of Giuliano.
-
C.
Lelia
Lelia is the given name of A'Lelia Walker, an influential African-American businesswoman and patron of the arts during the Harlem Renaissance.
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Licia
Licia is a shortened or diminutive form of the given name Felicia.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded315f14819085727bd9b4363d10 |
completed | April 2, 2026, 4:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32ad838b08190ab8c50a4108bba68 |
completed | April 6, 2026, 3:39 a.m. |
Created at: March 30, 2026, 9:11 p.m.