Triple
T14191808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Britain |
E351729
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Ron Goodwin |
E348324
|
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: Ron Goodwin | Statement: [Battle of Britain, composer, Ron Goodwin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ron Goodwin Context triple: [Battle of Britain, composer, Ron Goodwin]
-
A.
Ron Goodwin
chosen
Ron Goodwin was a British composer and conductor best known for his rousing film scores for war and adventure movies in the mid-20th century.
-
B.
Albert Weinert
Albert Weinert was a German-American sculptor and monument designer known for his public memorials in the United States.
-
C.
Michael Kamen
Michael Kamen was an American composer and conductor renowned for his film and television scores, including major works in action cinema and acclaimed historical dramas.
-
D.
Geoffrey Faithfull
Geoffrey Faithfull was a British cinematographer known for his work on numerous films from the silent era through the mid-20th century, including the classic science fiction horror film "Village of the Damned."
-
E.
John Debney
John Debney is an American film composer known for scoring a wide range of movies and television shows, including major studio productions and acclaimed dramas.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61df628c8190ba3f557e2128dce5 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d0a172c819096874f1bdd290cbb |
completed | May 8, 2026, 1:31 a.m. |
Created at: April 10, 2026, 1:04 a.m.