Triple
T21275916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Hurley |
E524386
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | So Much (for) Stardust |
—
|
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: So Much (for) Stardust | Statement: [Andrew Hurley, notableWork, So Much (for) Stardust]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: So Much (for) Stardust Context triple: [Andrew Hurley, notableWork, So Much (for) Stardust]
-
A.
So Much (for) Stardust
chosen
So Much (for) Stardust is a 2023 studio album by American rock band Fall Out Boy that blends their pop-punk roots with orchestral and experimental elements.
-
B.
Stardust
Stardust was a NASA Discovery Program mission that collected and returned samples from the coma of comet Wild 2 and interstellar dust to Earth for detailed laboratory analysis.
-
C.
Stardust
Stardust is a 1974 British musical drama film following the rise and fall of a rock star, serving as a sequel to the film "That'll Be the Day."
-
D.
Stardust
"Stardust" is a classic popular song, widely regarded as a jazz and American Songbook standard, famously interpreted by Louis Armstrong and many other artists.
-
E.
Stardust
Stardust is a fantasy novel by Neil Gaiman that blends fairy-tale romance and adventure in a magical realm bordering Victorian England.
- 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_69e0b516293c819089458ea2ec85f85e |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736577fd48190a0038a6ac5678668 |
completed | April 21, 2026, 8:33 a.m. |
Created at: April 16, 2026, 4:02 p.m.