Triple
T2216229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Vaughn |
E48037
|
entity |
| Predicate | producerOf |
P490
|
FINISHED |
| Object | Stardust |
E158659
|
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: Stardust | Statement: [Matthew Vaughn, producerOf, Stardust]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stardust Context triple: [Matthew Vaughn, producerOf, Stardust]
-
A.
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.
-
B.
Stardust
chosen
Stardust is a fantasy novel by Neil Gaiman that blends fairy-tale romance and adventure in a magical realm bordering Victorian England.
-
C.
Starlight
Starlight is a fictional character or element associated with the Evolver universe, likely representing a key component or aspect within that setting.
-
D.
Shine
Shine is a studio album by British R&B singer Estelle that showcases her blend of soul, hip hop, and pop influences.
-
E.
Shine
"Shine" is a pop song by British boy band Take That, known for its upbeat, retro-inspired sound and success as a major UK hit.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc00f4c3881909d03301fcdfa8b67 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71b811748190b985972a74c0355d |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:46 p.m.