Triple
T22665584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Boy (award) |
E559774
|
entity |
| Predicate | notableWinner |
P2766
|
FINISHED |
| Object | Gavi |
—
|
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: Gavi | Statement: [Golden Boy (award), notableWinner, Gavi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gavi Context triple: [Golden Boy (award), notableWinner, Gavi]
-
A.
Gavi
Gavi is a small, uninhabited island in Italy’s Pontine archipelago, known for its rugged coastline and protected natural environment.
-
B.
Gavi
chosen
Gavi is a Spanish professional footballer, known as a highly talented young midfielder for FC Barcelona and the Spain national team.
-
C.
Gavi, the Vaccine Alliance
Gavi, the Vaccine Alliance is a global health partnership that increases access to immunization in low-income countries by bringing together public and private sector resources.
-
D.
Nasar
Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
-
E.
Colta
Colta is a rural canton in Ecuador’s central highlands known for its indigenous communities, colonial history, and scenic Andean landscapes.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781b3dbc8190a312843cf8c1bfc6 |
completed | April 29, 2026, 3:16 a.m. |
Created at: April 17, 2026, 3:08 p.m.