Triple
T22496765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garret Lee |
E556160
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Garret Lee |
—
|
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: Garret Lee | Statement: [Garret Lee, name, Garret Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garret Lee Context triple: [Garret Lee, name, Garret Lee]
-
A.
Garret Lee
chosen
Garret Lee is an Irish music producer and mixer best known under the professional name Jacknife Lee, noted for his work with major rock and alternative bands.
-
B.
Garrett Lunceford
Garrett Lunceford is a member of the band Acceptance, an American rock group known for its melodic, emotionally driven sound.
-
C.
Garrett Fitzgerald
Garrett Fitzgerald is a notable individual whose name is associated with the surname Fitzgerald, potentially recognized for contributions in fields such as politics, academia, or public life.
-
D.
Garret Elkins
Garret Elkins is a film editor best known for his work on the stop-motion animated feature "Anomalisa."
-
E.
Garret Macy
Garret Macy is a central character in the crime drama series "Crossing Jordan," serving as the seasoned and often conflicted chief medical examiner who oversees Jordan Cavanaugh and her colleagues.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb2644c819094864bd88bcebcbd |
completed | April 29, 2026, 1:19 a.m. |
Created at: April 16, 2026, 8:50 p.m.