Triple
T13594939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudy Gekko |
E324792
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Winnie Gekko |
E324791
|
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: Winnie Gekko | Statement: [Rudy Gekko, relative, Winnie Gekko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Winnie Gekko Context triple: [Rudy Gekko, relative, Winnie Gekko]
-
A.
Winnie Gekko
chosen
Winnie Gekko is the daughter of fictional corporate raider Gordon Gekko in the "Wall Street" film series.
-
B.
Eric Falkenstein
Eric Falkenstein is a theater and film producer known for backing notable stage productions such as the play "Lucky Guy."
-
C.
Gob Bluth
Gob Bluth is a vain, inept magician and the frequently self-sabotaging eldest son of the Bluth family in the television sitcom "Arrested Development."
-
D.
Waring Hudsucker
Waring Hudsucker is a fictional industrial magnate whose dramatic death sets the plot in motion in the Coen brothers’ film "The Hudsucker Proxy."
-
E.
Gordon Gekko
Gordon Gekko is a fictional, ruthlessly ambitious corporate raider and symbol of 1980s Wall Street greed from the film "Wall Street."
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb057f1c881909a3bb77c659a724a |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bc762a08190b5d29cef9923da84 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.