Triple
T20103739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Walton Cooper |
E496614
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cooper |
—
|
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: Cooper | Statement: [Christopher Walton Cooper, familyName, Cooper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cooper Context triple: [Christopher Walton Cooper, familyName, Cooper]
-
A.
Cooper
Cooper is a central character in the science fiction horror film "Event Horizon," serving as a member of the rescue crew sent to investigate the reappearance of the experimental starship.
-
B.
Cooper
Cooper was a pioneering British Formula One constructor best known for popularizing rear-engined race cars and achieving championship success in the late 1950s and early 1960s.
-
C.
Cooper
Cooper is the internal codename used by Samsung for the Galaxy Ace smartphone model.
-
D.
Cooper
Cooper is the main protagonist and former NASA pilot in the science fiction film "Interstellar," who joins a space mission to secure humanity's survival.
-
E.
Cooper
chosen
Cooper is a common English surname of occupational origin, traditionally referring to a maker or repairer of wooden casks and barrels.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6667170a4819085d07a4188ded541 |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:27 p.m.