Triple
T23284295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doyle Brunson |
E588946
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Doyle |
—
|
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: Doyle | Statement: [Doyle Brunson, givenName, Doyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doyle Context triple: [Doyle Brunson, givenName, Doyle]
-
A.
Doyle
Doyle is an American horror punk guitarist best known as a longtime member of the Misfits and for his eponymous solo band.
-
B.
Doyle
chosen
Doyle is a common Irish-origin surname borne by numerous notable figures in literature, sports, politics, and entertainment.
-
C.
Doyle
Doyle is a half-demon seer from the TV series "Angel" who receives prophetic visions and becomes an early ally and friend of the main characters.
-
D.
Minta Doyle
Minta Doyle is a character in Virginia Woolf’s novel "To the Lighthouse," known as a lively young woman whose relationships and experiences reflect the book’s themes of love, change, and the passage of time.
-
E.
Doyle Devereux
Doyle Devereux is an American actor and television personality best known for playing the comedic bailiff on the courtroom reality show "Judge Mathis."
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196454b4c8190a797537ce8912241 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 4:58 p.m.