Triple
T10180886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laetitia |
E236777
|
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: [Laetitia, hasVariant, Leticia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leticia Context triple: [Laetitia, 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.
Lorena
Lorena is a city in the state of São Paulo, Brazil, known for hosting a campus of the University of São Paulo.
-
C.
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.
-
D.
Mia Ausa
Mia Ausa is a young, kind-hearted magician and the daughter of the Magic Guild's leader in the role-playing game Lunar: The Silver Star.
-
E.
Paola
Paola is a feminine given name of Latin origin commonly used in Spanish- and Italian-speaking countries.
- 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_69d301373a008190b8d39a8db4167e4f |
completed | April 6, 2026, 12:41 a.m. |
Created at: March 30, 2026, 9:11 p.m.