Triple
T12258715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Superstar |
E292166
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Slow Whine
Slow Whine is a track featured on the album "Superstar," known for its smooth, laid-back vibe and melodic style.
|
E972960
|
NE FINISHED |
How this triple was built (4 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: Slow Whine | Statement: [Superstar, hasPart, Slow Whine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slow Whine Context triple: [Superstar, hasPart, Slow Whine]
-
A.
Slow Wine
"Slow Wine" is an R&B song by the American group Tony! Toni! Toné! known for its smooth, romantic groove and soulful vocal harmonies.
-
B.
Slow Burn
"Slow Burn" is a critically acclaimed, introspective country-pop song by Kacey Musgraves that opens her album "Golden Hour" and reflects on taking life at an unhurried, reflective pace.
-
C.
Slow Burn
Slow Burn is a critically acclaimed Slate narrative podcast that revisits major political and cultural scandals in American history with deep, serialized reporting.
-
D.
Slow Burn
"Slow Burn" is a science fiction work by British critic and author David Langford, known for his sharp wit and inventive speculative ideas.
-
E.
Slow and Low
"Slow and Low" is a hard-hitting, old-school hip hop track by the Beastie Boys, known for its heavy beats, shouted vocals, and party-centric lyrics.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Slow Whine Triple: [Superstar, hasPart, Slow Whine]
Generated description
Slow Whine is a track featured on the album "Superstar," known for its smooth, laid-back vibe and melodic style.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Slow Whine Target entity description: Slow Whine is a track featured on the album "Superstar," known for its smooth, laid-back vibe and melodic style.
-
A.
Slow Wine
"Slow Wine" is an R&B song by the American group Tony! Toni! Toné! known for its smooth, romantic groove and soulful vocal harmonies.
-
B.
Slow Burn
"Slow Burn" is a critically acclaimed, introspective country-pop song by Kacey Musgraves that opens her album "Golden Hour" and reflects on taking life at an unhurried, reflective pace.
-
C.
Slow Burn
Slow Burn is a critically acclaimed Slate narrative podcast that revisits major political and cultural scandals in American history with deep, serialized reporting.
-
D.
Slow Burn
"Slow Burn" is a science fiction work by British critic and author David Langford, known for his sharp wit and inventive speculative ideas.
-
E.
Slow and Low
"Slow and Low" is a hard-hitting, old-school hip hop track by the Beastie Boys, known for its heavy beats, shouted vocals, and party-centric lyrics.
- F. None of above. chosen
Provenance (5 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ccadc3c81908fe68adc3fdcc851 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60abfc8588190ab9300c6e5e59092 |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f61a13fd1481908a06ca65b276e0e1 |
completed | May 2, 2026, 3:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f61ad2bd0c8190ada37bc1f8ae160f |
completed | May 2, 2026, 3:40 p.m. |
Created at: April 8, 2026, 9:52 p.m.