Triple
T13479399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch Wagenbach |
E318331
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Jay Karnes |
E392053
|
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: Jay Karnes | Statement: [Dutch Wagenbach, portrayedBy, Jay Karnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Karnes Context triple: [Dutch Wagenbach, portrayedBy, Jay Karnes]
-
A.
Jay Karnes
chosen
Jay Karnes is an American actor best known for his role as Detective Holland "Dutch" Wagenbach on the television crime drama series "The Shield."
-
B.
Jon Kern
Jon Kern is a software engineer and consultant best known as one of the original co-authors of the Agile Manifesto, helping to shape modern agile software development practices.
-
C.
Ken Kelsch
Ken Kelsch was an American cinematographer and occasional producer known for his gritty visual style and frequent collaborations with director Abel Ferrara.
-
D.
Kevin Biegel
Kevin Biegel is an American television writer and producer best known for co-creating the sitcom Cougar Town and working on shows like Scrubs and Enlisted.
-
E.
Kevin Hageman
Kevin Hageman is an American screenwriter and producer known for his work on animated and family films and television series, including contributions to The Lego Movie franchise.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf266c508190930d30776c09ce35 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d8c942481909858e340944ed57c |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:42 p.m.