Triple
T19994617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A.W.O.L. |
E494158
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Magic Hour |
—
|
NE NERFINISHED |
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: Magic Hour | Statement: [A.W.O.L., hasPart, Magic Hour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magic Hour Context triple: [A.W.O.L., hasPart, Magic Hour]
-
A.
Magic Hour
chosen
"Magic Hour" is a musical work by American songwriter and producer Scott Hoffman, better known as Babydaddy of the pop band Scissor Sisters.
-
B.
Golden Hour
Golden Hour is a critically acclaimed, genre-blending country-pop album by Kacey Musgraves that won the Grammy Award for Album of the Year.
-
C.
Blue Hour
Blue Hour is a novel by American author James Leo Herlihy, known for its introspective exploration of human relationships and emotional turmoil.
-
D.
The Golden Hour
The Golden Hour is a novel by British author William Nicholson that intertwines personal drama and historical events in a reflective, character-driven narrative.
-
E.
The Magic Hour
The Magic Hour is a segment or component of the podcast "Radio Silence," likely featuring a distinct thematic focus or format within the show.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe306548190a6924ce3798a4d3d |
completed | April 20, 2026, 5:18 p.m. |
Created at: April 11, 2026, 3:31 p.m.