Triple
T21537893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benchley family |
E531398
|
entity |
| Predicate | hasNotableMember |
P304
|
FINISHED |
| Object | Nathaniel Benchley |
—
|
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: Nathaniel Benchley | Statement: [Benchley family, hasNotableMember, Nathaniel Benchley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathaniel Benchley Context triple: [Benchley family, hasNotableMember, Nathaniel Benchley]
-
A.
Nathaniel Benchley
chosen
Nathaniel Benchley was an American author and screenwriter known for his humorous novels and stories, several of which were adapted into popular films.
-
B.
Peter Benchley
Peter Benchley was an American author and screenwriter best known for writing the novel "Jaws," which was adapted into the iconic 1975 film.
-
C.
Peter Heller
Peter Heller is a British DJ, remixer, and record producer best known for his influential work in house music during the 1990s and 2000s.
-
D.
Stephen Badger
Stephen Badger is a film producer known for his work on the acclaimed music documentary "Muscle Shoals."
-
E.
Stephen Curwick
Stephen Curwick is a screenwriter best known for his work on the comedy film series "Police Academy," including "Police Academy 5: Assignment Miami Beach."
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0fdf448190b47ac7c28904f86b |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.