Triple
T10470533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Die Another Day |
E246910
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Jinx Johnson |
E418762
|
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: Jinx Johnson | Statement: [Die Another Day, character, Jinx Johnson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jinx Johnson Context triple: [Die Another Day, character, Jinx Johnson]
-
A.
Jinx Johnson
chosen
Jinx Johnson is a daring and highly skilled NSA operative who partners with James Bond in the film "Die Another Day."
-
B.
Janelle Johnson
Janelle Johnson is an American actress best known for her work in mid-20th-century film and television and as the wife of actor David Nelson.
-
C.
Vickie Johnson
Vickie Johnson is a former WNBA guard and experienced professional basketball coach who has led multiple teams in the league.
-
D.
Jinx Godfrey
Jinx Godfrey is a British film editor best known for her work on acclaimed documentaries and feature films, including the Oscar-winning "Man on Wire."
-
E.
Antoinette Pettyjohn
Antoinette Pettyjohn is best known as the wife of the late American actor Yaphet Kotto.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509305fec81908b1acd91ae1f875d |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8a0094910819094d492c87b31898e |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:20 p.m.