Triple
T29068890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Mercy |
E735758
|
entity |
| Predicate | featuresEarlyStyleOf |
P112333
|
FINISHED |
| Object | Daddy Yankee |
—
|
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: Daddy Yankee | Statement: [No Mercy, featuresEarlyStyleOf, Daddy Yankee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresEarlyStyleOf Context triple: [No Mercy, featuresEarlyStyleOf, Daddy Yankee]
-
A.
showcasesEarlyStyleOf
chosen
Indicates that one entity exemplifies or displays the characteristic early style or formative phase of another entity.
-
B.
featuresStyle
Indicates that one entity exhibits, incorporates, or is characterized by a particular style associated with another entity.
-
C.
architecturalStyle
Indicates the architectural design tradition, movement, or style that characterizes the form and appearance of a structure or built work.
-
D.
artisticCharacteristic
Indicates that one entity possesses or exhibits a particular artistic quality, style, or trait in relation to another.
-
E.
heritageStyle
Indicates that one entity is characterized by, designed in, or associated with a particular heritage or traditional style defined by the other entity.
- 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69ff0491409c8190be40f633a58da0b1 |
completed | May 9, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69ff040bb5cc81909534c7eee85d5e90 |
completed | May 9, 2026, 9:53 a.m. |
Created at: April 28, 2026, 10:19 a.m.