Triple
T10688000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Charlesworth |
E251930
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Nick Barton |
E217588
|
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: Nick Barton | Statement: [Brian Charlesworth, notableStudent, Nick Barton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick Barton Context triple: [Brian Charlesworth, notableStudent, Nick Barton]
-
A.
Nick Barton
chosen
Nick Barton is a prominent evolutionary biologist known for his influential work on the genetics of adaptation and speciation.
-
B.
Sean Barton
Sean Barton is a film editor known for his work on various feature films, including the drama "Tea with Mussolini."
-
C.
Michael Barnathan
Michael Barnathan is an American film producer known for working on major studio hits such as the "Night at the Museum" series and the "Harry Potter" films.
-
D.
Chris Bacon
Chris Bacon is an American film and television composer known for scoring projects such as the psychological horror series "Bates Motel."
-
E.
Tony Britton
Tony Britton was a British actor known for his extensive work in film, television, and theatre from the mid-20th century onward.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd19f0f481909eeaa75d17d9c060 |
completed | April 9, 2026, 1:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff777c63c8190a989d33e8460bc2f |
completed | April 15, 2026, 8:39 p.m. |
Created at: April 8, 2026, 9:11 p.m.