Triple
T10737530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen and Country |
E253230
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Bill Rohan |
E928142
|
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: Bill Rohan | Statement: [Queen and Country, mainCharacter, Bill Rohan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Rohan Context triple: [Queen and Country, mainCharacter, Bill Rohan]
-
A.
Bill Rohan
chosen
Bill Rohan is the central character in the British film "Queen and Country," depicted as a young man navigating military service and personal growth in post-World War II England.
-
B.
Bob O'Brien
Bob O'Brien is a fictional universe created by author Kim Carter, serving as the setting for her imaginative stories and characters.
-
C.
Phil Burke
Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
-
D.
Michael O’Rourke
Michael O’Rourke is best known as the father of the late child actress Heather O’Rourke, who starred in the "Poltergeist" film series.
-
E.
Michael O’Rourke
Michael O’Rourke is an Irish media entrepreneur best known as a co-founder of the international sports television network Setanta Sports.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710410a04819090036597ac0d271c |
completed | April 9, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e623a9711081908eac4238a717305c |
completed | April 20, 2026, 1:01 p.m. |
Created at: April 8, 2026, 9:14 p.m.