Triple
T20444874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marshall Grant |
E501491
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Marshall Garnett Grant |
—
|
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: Marshall Garnett Grant | Statement: [Marshall Grant, fullName, Marshall Garnett Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marshall Garnett Grant Context triple: [Marshall Grant, fullName, Marshall Garnett Grant]
-
A.
Marshall Grant
chosen
Marshall Grant was an American upright bassist best known for being a longtime member of Johnny Cash’s backing band, the Tennessee Three.
-
B.
Marshall Lee
Marshall Lee is the gender-swapped vampire counterpart of Marceline from the animated series Adventure Time, appearing in the Fionna and Cake universe.
-
C.
Marshall Owen Roberts
Marshall Owen Roberts was a prominent 19th-century American shipping magnate and financier known for his role in maritime commerce and major infrastructure ventures.
-
D.
Marshall Harvey
Marshall Harvey is a film editor best known for his work on movies such as the dark comedy "The 'Burbs."
-
E.
Holter Graham
Holter Graham is an American actor and audiobook narrator known for voicing numerous popular titles across fiction and non-fiction.
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfca4788190ad57ecb504f54d11 |
completed | April 20, 2026, 8:30 p.m. |
Created at: April 16, 2026, 11:32 a.m.