Triple
T7594856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Living Daylights |
E179832
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Geoffrey Keen
Geoffrey Keen was a British character actor best known for his recurring role as the Minister of Defence in the James Bond film series.
|
E674765
|
NE FINISHED |
How this triple was built (4 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: Geoffrey Keen | Statement: [The Living Daylights, starring, Geoffrey Keen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geoffrey Keen Context triple: [The Living Daylights, starring, Geoffrey Keen]
-
A.
Rupert Macabee
Rupert Macabee is a character in the 1957 Charlie Chaplin film "A King in New York," appearing in its satirical portrayal of politics and media in postwar America.
-
B.
Roland Caulder
Roland Caulder is an actor known for his role in the film "The Iron Mask."
-
C.
John McGuffin
John McGuffin was a Northern Irish civil rights activist and writer known for his involvement in radical politics and his membership in the People's Democracy movement.
-
D.
Simon Dunsdon
Simon Dunsdon is a cinematographer known for his work on the animated film "Hotel Transylvania 3: Summer Vacation."
-
E.
Howard Bannister
Howard Bannister is the mild-mannered, musicologist protagonist played by Ryan O'Neal in the screwball comedy film "What's Up, Doc?".
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Geoffrey Keen Triple: [The Living Daylights, starring, Geoffrey Keen]
Generated description
Geoffrey Keen was a British character actor best known for his recurring role as the Minister of Defence in the James Bond film series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Geoffrey Keen Target entity description: Geoffrey Keen was a British character actor best known for his recurring role as the Minister of Defence in the James Bond film series.
-
A.
Rupert Macabee
Rupert Macabee is a character in the 1957 Charlie Chaplin film "A King in New York," appearing in its satirical portrayal of politics and media in postwar America.
-
B.
Roland Caulder
Roland Caulder is an actor known for his role in the film "The Iron Mask."
-
C.
John McGuffin
John McGuffin was a Northern Irish civil rights activist and writer known for his involvement in radical politics and his membership in the People's Democracy movement.
-
D.
Simon Dunsdon
Simon Dunsdon is a cinematographer known for his work on the animated film "Hotel Transylvania 3: Summer Vacation."
-
E.
Howard Bannister
Howard Bannister is the mild-mannered, musicologist protagonist played by Ryan O'Neal in the screwball comedy film "What's Up, Doc?".
- F. None of above. chosen
Provenance (5 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_69c69f3487ec8190bf7acdf2dd91e6d6 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9bbcd8081909a229d7faa2ffdc8 |
completed | March 27, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8619d6f2081908c8b589d4106691f |
completed | March 28, 2026, 11:17 p.m. |
| NEDg | Description generation | batch_69c86211e4f88190b38bce6441e33b53 |
completed | March 28, 2026, 11:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c862bb95e881909a60608a5279238d |
completed | March 28, 2026, 11:22 p.m. |
Created at: March 27, 2026, 3:53 p.m.