Triple
T12685965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Sloane |
E303065
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Max Richter |
E619803
|
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: Max Richter | Statement: [Miss Sloane, musicBy, Max Richter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Max Richter Context triple: [Miss Sloane, musicBy, Max Richter]
-
A.
Max Richter
chosen
Max Richter is a German-British composer known for his influential contemporary classical and minimalist film scores and solo works.
-
B.
Owen Pallett
Owen Pallett is a Canadian composer, violinist, and singer-songwriter known for his intricate orchestral pop arrangements and collaborations with numerous indie rock artists.
-
C.
Jóhann Jóhannsson
Jóhann Jóhannsson was an Icelandic composer and musician renowned for his atmospheric, minimalist film scores and experimental solo works.
-
D.
Yann Tiersen
Yann Tiersen is a French musician and composer best known internationally for his whimsical, minimalist score to the film "Amélie."
-
E.
Daniel Lopatin
Daniel Lopatin is an American electronic musician and producer, best known for his work as Oneohtrix Point Never and his experimental film scores.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961d7cd4c81909521839ef5859799 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671a8f068819086e2191439607f76 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:21 p.m.