Triple
T3760168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City Slickers |
E82141
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Bruno Kirby |
E286425
|
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: Bruno Kirby | Statement: [City Slickers, starring, Bruno Kirby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bruno Kirby Context triple: [City Slickers, starring, Bruno Kirby]
-
A.
Bruno Kirby
chosen
Bruno Kirby was an American character actor known for his memorable supporting roles in films such as "When Harry Met Sally...," "City Slickers," and "Good Morning, Vietnam."
-
B.
Ben Daimio
Ben Daimio is a former U.S. Marine turned scarred, resurrected field leader in the Hellboy universe’s B.P.R.D., known for his volatile temperament and hidden monstrous curse.
-
C.
Kenta Izumi
Kenta Izumi is a Japanese politician who serves as the leader of the main opposition force, the Constitutional Democratic Party of Japan.
-
D.
Daisuke
Daisuke is a common Japanese masculine given name used by various notable figures in entertainment, sports, and other fields.
-
E.
Shinya
Shinya is a Japanese given name commonly used for males.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc3d3f48190974cec104080949f |
completed | March 8, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f0321c4c8190ba372148c483c4ca |
completed | March 14, 2026, 5:20 a.m. |
Created at: March 8, 2026, 3:35 p.m.