Triple
T2406241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The King’s Man |
E50281
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Gemma Arterton |
E204776
|
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: Gemma Arterton | Statement: [The King’s Man, stars, Gemma Arterton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gemma Arterton Context triple: [The King’s Man, stars, Gemma Arterton]
-
A.
Gemma Arterton
chosen
Gemma Arterton is an English actress known for her roles in films such as "St Trinian's," "Quantum of Solace," and "Prince of Persia: The Sands of Time."
-
B.
Eva Green
Eva Green is a French actress known for her dark, intense performances in film and television, including prominent roles in projects like "Casino Royale" and "Penny Dreadful."
-
C.
Kate O’Flynn
Kate O’Flynn is a British actress known for her work in film, television, and theatre, including a role in the romantic comedy sequel "Bridget Jones’s Baby."
-
D.
Margot Tennant
Margot Tennant, later Margot Asquith, was a prominent British socialite, author, and wit who became the influential second wife of Prime Minister H. H. Asquith.
-
E.
Rebecca Ferguson
Rebecca Ferguson is a Swedish actress known for her versatile performances in films such as the Mission: Impossible series, The Greatest Showman, and Dune.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc8fb78408190b99fa8b4dfaaa75d |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf403f74819082dc50e31f29b171 |
completed | March 9, 2026, 12:38 p.m. |
Created at: March 4, 2026, 7:58 p.m.