Triple
T22379569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koa (65) |
E553234
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Bryan Woods |
—
|
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: Bryan Woods | Statement: [Koa (65), createdBy, Bryan Woods]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bryan Woods Context triple: [Koa (65), createdBy, Bryan Woods]
-
A.
Bryan Woods
chosen
Bryan Woods is an American screenwriter and filmmaker best known for co-writing the hit horror film "A Quiet Place."
-
B.
Bryan Devendorf
Bryan Devendorf is an American drummer best known as a founding member and rhythmic backbone of the indie rock band The National.
-
C.
Bryan Burk
Bryan Burk is an American film and television producer best known for his collaborations with J.J. Abrams on projects such as Lost, Star Trek, and Mission: Impossible.
-
D.
Brian Swardstrom
Brian Swardstrom is a prominent American talent agent and partner at United Talent Agency, known for representing acclaimed actors and filmmakers.
-
E.
Brent Erickson
Brent Erickson is a composer and musician known for creating the musical score for the animated short film "Tin Toy."
- 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_69e11e4c03248190a26a5060ea6973ee |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582afe6c819093940f9d817c64a8 |
completed | April 29, 2026, 1 a.m. |
Created at: April 16, 2026, 8:45 p.m.