Triple
T18163854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilberto |
E434837
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Beto |
—
|
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: Beto | Statement: [Gilberto, hasDiminutive, Beto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beto Context triple: [Gilberto, hasDiminutive, Beto]
-
A.
Beto
chosen
Beto is an American politician from Texas known for his high-profile campaigns for the U.S. Senate and the presidency.
-
B.
Beto
Beto is a main Muppet character from the Mexican children's television show Plaza Sésamo, known as the serious, responsible counterpart to his best friend Enrique.
-
C.
Jair
Jair is a minor biblical judge of Israel mentioned in the Book of Judges, known for his leadership and his thirty sons who rode thirty donkeys and controlled thirty towns.
-
D.
Darlan
Darlan is a French surname most notably associated with François Darlan, a prominent admiral and political figure in Vichy France during World War II.
-
E.
Berto
Berto is a diminutive or short given name commonly used as an affectionate or informal form of longer names such as Humbert.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec55a088190868ee0b0a310fefb |
completed | April 19, 2026, 1:55 p.m. |
Created at: April 10, 2026, 10:30 a.m.