Triple
T3765281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samsonite Man |
E82659
|
entity |
| Predicate | hasMusicalGenreCharacteristic |
P45796
|
FINISHED |
| Object | contemporary R&B |
—
|
LITERAL 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: contemporary R&B | Statement: [Samsonite Man, hasMusicalGenreCharacteristic, contemporary R&B]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMusicalGenreCharacteristic Context triple: [Samsonite Man, hasMusicalGenreCharacteristic, contemporary R&B]
-
A.
hasMusicalStyleCharacteristic
chosen
Indicates that something possesses or exhibits a particular musical style as a defining characteristic.
-
B.
hasMusical
Indicates that one entity features, includes, or is associated with a musical work, performance, or musical component.
-
C.
hasMusicCharacteristic
Indicates that an entity possesses a specific musical feature, quality, or attribute.
-
D.
musicalAttribute
Indicates a relationship where a musical work, performance, or element is characterized by a specific musical property or quality (such as tempo, key, style, or mood).
-
E.
hasMusicalForm
Indicates that one entity (typically a musical work or piece) is characterized by or structured according to a particular musical form.
- F. None of above.
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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbfeb52081909c38103beb5dbdcd |
completed | March 8, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.