Triple
T17217543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man with the Golden Gun (film) |
E417890
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Roger Moore |
E105584
|
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: Roger Moore | Statement: [The Man with the Golden Gun (film), stars, Roger Moore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roger Moore Context triple: [The Man with the Golden Gun (film), stars, Roger Moore]
-
A.
Roger Moore
chosen
Roger Moore was an English actor best known for playing James Bond in seven films from 1973 to 1985.
-
B.
George Lazenby
George Lazenby is an Australian actor best known for playing James Bond in the 1969 film "On Her Majesty's Secret Service."
-
C.
Timothy Dalton
Timothy Dalton is a British actor best known for portraying James Bond in the films "The Living Daylights" and "Licence to Kill."
-
D.
Robert Vaughn
Robert Vaughn was an American actor best known for his suave, sophisticated roles in film and television, particularly as Napoleon Solo in the 1960s series "The Man from U.N.C.L.E."
-
E.
Sean Connery
Sean Connery was a Scottish actor best known for originating the role of James Bond on film and for his distinguished career in both mainstream and critically acclaimed cinema.
- 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_69d886d779488190b131369541c04e7d |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42ddb2b148190b3b50572cc285e3d |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01675381a0819094ed04eac636440b |
completed | May 11, 2026, 5:21 a.m. |
Created at: April 10, 2026, 5:38 a.m.