Triple
T4432762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jake Cherry |
E95371
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jake Cherry |
E95371
|
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: Jake Cherry | Statement: [Jake Cherry, name, Jake Cherry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake Cherry Context triple: [Jake Cherry, name, Jake Cherry]
-
A.
Jake Cherry
chosen
Jake Cherry is an American actor best known for playing Nick Daley, the son of Ben Stiller’s character, in the film "Night at the Museum" and its sequels.
-
B.
Chris Chasse
Chris Chasse is an American guitarist best known for his tenure with the punk rock band Rise Against during the early 2000s.
-
C.
Jack Driscoll
Jack Driscoll is a central heroic character in the 1933 film "King Kong," serving as the ship's first mate and the primary human protagonist who helps rescue Ann Darrow from the giant ape.
-
D.
Charlie Norwood
Charlie Norwood was a U.S. Congressman from Georgia and a dentist by profession, known for his work on healthcare and veterans’ issues.
-
E.
Kevin Chapman
Kevin Chapman is an American actor known for his tough, blue-collar character roles in film and television, including prominent parts in series like "Person of Interest" and "City on a Hill."
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3556cd83881908547aa311c4f17fa |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6137171148190b77a6f783d5cf315 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:31 p.m.