Triple
T11887542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Dietzen |
E282826
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Brian Dietzen |
E282826
|
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 Dietzen | Statement: [Brian Dietzen, name, Brian Dietzen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Dietzen Context triple: [Brian Dietzen, name, Brian Dietzen]
-
A.
Brian Dietzen
chosen
Brian Dietzen is an American actor best known for playing medical examiner Jimmy Palmer on the long-running television series NCIS.
-
B.
Scott Dietzen
Scott Dietzen is a technology executive and entrepreneur best known as the founding CEO of Pure Storage, a leading enterprise data storage company.
-
C.
Brian Bockrath
Brian Bockrath is a television producer best known for his executive production work on the post-apocalyptic horror drama series The Walking Dead: Dead City.
-
D.
Matt Oberg
Matt Oberg is an American actor and comedian known for his work in television comedies and voice acting roles.
-
E.
Brian Krause
Brian Krause is an American actor best known for playing the whitelighter Leo Wyatt on the television series "Charmed."
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a13370819086386fecb99e4f0b |
completed | April 10, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a74cd8c8190a1b2aac622b11edc |
completed | May 2, 2026, 4:46 p.m. |
Created at: April 8, 2026, 9:44 p.m.