Triple
T3292287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slow Horses |
E69128
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Daniel Pemberton |
E79203
|
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: Daniel Pemberton | Statement: [Slow Horses, composer, Daniel Pemberton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Pemberton Context triple: [Slow Horses, composer, Daniel Pemberton]
-
A.
Daniel Pemberton
chosen
Daniel Pemberton is a British composer known for his innovative and eclectic film scores across major Hollywood and independent productions.
-
B.
Lorne Balfe
Lorne Balfe is a Scottish composer and producer known for his work on major film, television, and video game scores, often in the action and blockbuster genres.
-
C.
Michael Abels
Michael Abels is an American composer best known for his innovative, genre-blending film scores for Jordan Peele’s movies, including Get Out, Us, and Nope.
-
D.
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.
-
E.
Rupert Gregson-Williams
Rupert Gregson-Williams is a British film and television composer known for scoring major Hollywood productions such as "Wonder Woman," "Aquaman," and "The Crown."
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb07379dc8190b7bb409bcf42bdd6 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3cfec98819094208d2cb6e459ea |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.