Triple
T14128762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Van Holt |
E340103
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Brian Van Holt |
E340103
|
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: Brian Van Holt | Statement: [Brian Van Holt, name, Brian Van Holt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Van Holt Context triple: [Brian Van Holt, name, Brian Van Holt]
-
A.
Brian Van Holt
chosen
Brian Van Holt is an American actor known for his roles in films like "Black Hawk Down" and "Den of Thieves" as well as the TV series "Cougar Town."
-
B.
Lee Zahler
Lee Zahler was an American film composer and musical director known for scoring numerous serials and B-movies during the 1930s and 1940s.
-
C.
John Seitz
John Seitz was an American cinematographer renowned for his influential work in classic Hollywood cinema, particularly in film noir and science fiction.
-
D.
Tom Hiel
Tom Hiel is an American film and television composer known for scoring a variety of genre projects, including cult and horror films.
-
E.
Ron Jensen
Ron Jensen is an American politician who has served as the mayor of Grand Prairie, Texas.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6098013c8190b1bac9d3fff60acd |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19356478819083406440c22c38e2 |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 9, 2026, 10:23 p.m.