Triple
T21900329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Tadross |
E540789
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Cliffhanger |
—
|
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: Cliffhanger | Statement: [Michael Tadross, notableWork, Cliffhanger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cliffhanger Context triple: [Michael Tadross, notableWork, Cliffhanger]
-
A.
Cliffhanger
chosen
Cliffhanger is a 1993 action thriller film starring Sylvester Stallone as a mountain climber caught in a high-altitude heist gone wrong.
-
B.
Under Siege
Under Siege is a 1992 action thriller film starring Steven Seagal as a former Navy SEAL battling terrorists aboard a U.S. battleship.
-
C.
Under Siege
Under Siege is a recurring professional wrestling event produced by the American promotion Impact Wrestling.
-
D.
The Tremblers
The Tremblers were a short-lived early 1980s rockabilly/new wave side project led by Peter Noone of Herman’s Hermits.
-
E.
Cliff Hangers
Cliff Hangers is a popular mountain-climbing themed pricing game on the long-running television game show "The Price Is Right," where a yodeling climber ascends a cliff based on contestants’ pricing accuracy.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fca2bf88190b2a5b912aa102513 |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:07 p.m.