Triple
T15430522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letizia |
E369625
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Leticia |
E307981
|
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: Leticia | Statement: [Letizia, hasVariant, Leticia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leticia Context triple: [Letizia, hasVariant, Leticia]
-
A.
Leticia
chosen
Leticia is a remote Colombian city on the Amazon River, known as a key gateway to the Amazon rainforest and a tri-border point with Brazil and Peru.
-
B.
Leticia Brédice
Leticia Brédice is an Argentine actress known for her intense, often edgy performances in film, television, and theater.
-
C.
Corica
Corica is a surname most notably associated with Australian former soccer player and coach Steve Corica.
-
D.
Lorena
Lorena is a city in the state of São Paulo, Brazil, known for hosting a campus of the University of São Paulo.
-
E.
Cecilia Lisbon
Cecilia Lisbon is the youngest and most enigmatic of the Lisbon sisters in Jeffrey Eugenides' novel "The Virgin Suicides," whose tragic fate sets the tone for the story's haunting exploration of adolescence and suburban malaise.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ed8ea888190bff8dc14859cca31 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a827d9081909fabc48bc685ba5b |
completed | May 9, 2026, 11:29 a.m. |
Created at: April 10, 2026, 3:21 a.m.