Triple
T14540810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dreamland |
E341162
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Hot Sugar |
E368241
|
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: Hot Sugar | Statement: [Dreamland, hasPart, Hot Sugar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hot Sugar Context triple: [Dreamland, hasPart, Hot Sugar]
-
A.
Hot Sugar
chosen
Hot Sugar is an experimental electronic music producer known for creating textured, sample-based compositions often built from unconventional found sounds.
-
B.
Too Sweet
"Too Sweet" is a soulful, blues-inflected song by Irish singer-songwriter Hozier that explores themes of desire, temptation, and moral conflict.
-
C.
Hot Stuff
"Hot Stuff" is a 1979 disco hit by Donna Summer that blends dance rhythms with rock influences and became one of her signature songs.
-
D.
Big Sugar
Big Sugar is a Canadian rock band known for its heavy, blues-influenced sound and fusion of rock, reggae, and dub styles.
-
E.
Sweetener
Sweetener is Ariana Grande's critically acclaimed fourth studio album, noted for its blend of pop and R&B with innovative production and themes of healing and empowerment.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1bd0dd4819094c8b2f2aa6b1c5e |
completed | April 14, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a5cca788190aa8762d860c78721 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.