Triple
T10153257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane Keaton |
E232702
|
entity |
| Predicate | adoptedChildren |
P40227
|
FINISHED |
| Object | Dexter Keaton |
E843525
|
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: Dexter Keaton | Statement: [Diane Keaton, adoptedChildren, Dexter Keaton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dexter Keaton Context triple: [Diane Keaton, adoptedChildren, Dexter Keaton]
-
A.
Dexter Keaton
chosen
Dexter Keaton is the adopted daughter of acclaimed American actress and filmmaker Diane Keaton.
-
B.
John Derek
John Derek was an American actor, director, and photographer known for his roles in mid-20th-century Hollywood films and later for directing and photographing his wife Bo Derek.
-
C.
Jack Deerson
Jack Deerson is a cinematographer best known for his work on the 1971 road movie "Two-Lane Blacktop."
-
D.
Dexter Horton
Dexter Horton was a pioneering Seattle banker best known for founding the city's first successful bank, which later evolved into part of Wells Fargo.
-
E.
Duke Keaton
Duke Keaton is one of the adopted children of acclaimed American actress and filmmaker Diane Keaton.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec376cd48190990862c56c3a4dce |
completed | April 2, 2026, 4:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300a40638819082e575d957711377 |
completed | April 6, 2026, 12:39 a.m. |
Created at: March 30, 2026, 9:08 p.m.