Triple
T11009701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Starkey |
E260214
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Starkey |
E321074
|
NE FINISHED |
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: Starkey | Statement: [Lee Starkey, familyName, Starkey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Starkey Context triple: [Lee Starkey, familyName, Starkey]
-
A.
Starkey
chosen
Starkey is a surname most prominently associated with British historian and television personality David Starkey.
-
B.
Mavado
Mavado is a Jamaican dancehall and reggae artist known for his gritty vocal style and influential role in modern dancehall music.
-
C.
Ziggy Marley
Ziggy Marley is a Grammy-winning Jamaican musician and the eldest son of reggae legend Bob Marley, known for his work with Ziggy Marley and the Melody Makers and his solo career.
-
D.
Skip Marley
Skip Marley is a Jamaican singer-songwriter and grandson of reggae legend Bob Marley, known for blending reggae with pop and contemporary influences.
-
E.
Pev Marley
Pev Marley was the husband of American film actress Linda Darnell, known primarily for his marriage to the Hollywood star.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79788d44c819084f35693ed96f422 |
completed | April 9, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a97587708190bf31976a3fbc1015 |
completed | April 18, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:25 p.m.