Triple
T13021132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Gekko |
E326172
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Gordon Gekko |
E64381
|
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: Gordon Gekko | Statement: [Kate Gekko, associatedWith, Gordon Gekko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gordon Gekko Context triple: [Kate Gekko, associatedWith, Gordon Gekko]
-
A.
Gordon Gekko
chosen
Gordon Gekko is a fictional, ruthlessly ambitious corporate raider and symbol of 1980s Wall Street greed from the film "Wall Street."
-
B.
Logan Roy
Logan Roy is the ruthless, aging media mogul and patriarch of the Roy family in the television series "Succession," whose control over his empire drives the show's central power struggles.
-
C.
Eric Falkenstein
Eric Falkenstein is a theater and film producer known for backing notable stage productions such as the play "Lucky Guy."
-
D.
Lloyd Vogel
Lloyd Vogel is the fictional, emotionally troubled journalist protagonist of the film "A Beautiful Day in the Neighborhood," whose life is transformed through his encounters with Fred Rogers.
-
E.
Michael Milken
Michael Milken is an American financier and philanthropist best known for pioneering the high-yield “junk bond” market and later founding influential economic and public policy initiatives.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecf21bc819082fb512bc479b4be |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d5f861188190892b4d693395cc5e |
completed | May 3, 2026, 4:58 a.m. |
Created at: April 9, 2026, 8:52 p.m.