Triple
T21615051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jarrett |
E533415
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Garrett |
—
|
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: Garrett | Statement: [Jarrett, hasVariant, Garrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garrett Context triple: [Jarrett, hasVariant, Garrett]
-
A.
Garrett
chosen
Garrett is a masculine given name of Old French and Germanic origin, commonly used in English-speaking countries.
-
B.
Garrett Dutton
Garrett Dutton, better known by his stage name G. Love, is an American musician and frontman recognized for blending blues, hip hop, and alternative rock.
-
C.
Gavin
Gavin is a masculine given name of Celtic origin, commonly used in English-speaking countries.
-
D.
Gaven
Gaven is a suburb on the Gold Coast in Queensland, Australia, known for its semi-rural character and proximity to major transport routes.
-
E.
Garrett Walker
Garrett Walker is the fictional President of the United States in the political drama series "House of Cards," whose administration becomes entangled in the ruthless schemes of Frank Underwood.
- 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_69e0c46411108190bba0d4176dffc9f3 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3ba9aca48190b5180eefd61a9fdc |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 16, 2026, 6:33 p.m.