Triple
T22930990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leandro Barbosa |
E569438
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Leandro |
—
|
NE NERFINISHED |
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: Leandro | Statement: [Leandro Barbosa, givenName, Leandro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leandro Context triple: [Leandro Barbosa, givenName, Leandro]
-
A.
Leandro
Leandro is a fictional character portrayed by British actor Ariyon Bakare, known from his work in film and television.
-
B.
Leandro
chosen
Leandro is the given first name of Argentine jazz saxophonist and composer Gato Barbieri.
-
C.
Marcelo
Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
-
D.
Marcelo
Marcelo is a surname most prominently associated with Sheila Lirio Marcelo, the Filipino-American entrepreneur who founded the caregiving platform Care.com.
-
E.
Marcio
Marcio is a masculine given name commonly used in Portuguese- and Spanish-speaking countries, derived from the Latin name Marcius.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458f7d008190901dccbaebeaba24 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18131956c8190b8c850fc1d57a119 |
completed | April 29, 2026, 3:55 a.m. |
Created at: April 17, 2026, 3:44 p.m.