Triple
T21542933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naked City |
E531539
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Paul Burke |
—
|
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: Paul Burke | Statement: [Naked City, starring, Paul Burke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Burke Context triple: [Naked City, starring, Paul Burke]
-
A.
Paul Burke
chosen
Paul Burke was an American actor best known for his television roles in series like "Naked City" and "12 O'Clock High," as well as appearances in notable films of the 1960s.
-
B.
Paul Burke
Paul Burke is a musician best known as a member of the Scottish alternative rock band Beecake.
-
C.
Phil Burke
Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
-
D.
David J. Burke
David J. Burke is a television producer and writer best known for his work as an executive producer on the science fiction series SeaQuest DSV.
-
E.
Michael Buckley
Michael Buckley is a common name shared by several notable individuals, including authors, entertainers, and public figures across different fields.
- 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_69e0c45f17148190949c330ab9c27706 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeb58c34808190b0eb54ba01e2cc13 |
completed | April 27, 2026, 1:02 a.m. |
Created at: April 16, 2026, 6:28 p.m.