Triple
T19734479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Corbett |
E473940
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Bo Derek |
—
|
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: Bo Derek | Statement: [John Corbett, spouse, Bo Derek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bo Derek Context triple: [John Corbett, spouse, Bo Derek]
-
A.
Bo Derek
chosen
Bo Derek is an American actress and model best known for her breakout role in the 1979 film "10," which made her a major sex symbol of the late 20th century.
-
B.
Salman Khan
Salman Khan is an American educator and entrepreneur best known as the founder of the online learning platform Khan Academy.
-
C.
Salman Khan
Salman Khan is a major Indian film actor and producer, known for his blockbuster Hindi movies, larger-than-life screen persona, and significant influence on Bollywood popular culture.
-
D.
Sunny Deol
Sunny Deol is an Indian film actor, director, and politician best known for his powerful action roles and intense performances in Hindi cinema.
-
E.
Jeetendra
Jeetendra is a veteran Indian film and television actor best known for his prolific work in Hindi cinema from the 1960s through the 1990s and his energetic dance-oriented roles.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6515b4d308190af3be1787fa7c65b |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.