Triple
T33067312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Perdón |
E846135
|
entity |
| Predicate | usesUrbanLatinStyle |
P175770
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [El Perdón, usesUrbanLatinStyle, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesUrbanLatinStyle Context triple: [El Perdón, usesUrbanLatinStyle, true]
-
A.
hasUrbanTrend
Indicates that something exhibits characteristics, patterns, or influences associated with urban environments or city-oriented lifestyles.
-
B.
footworkStyle
Indicates the specific manner or technique of how an entity moves or positions its feet within a particular activity or context.
-
C.
inTheStyleOf
Indicates that one entity is created, performed, or presented in a manner that imitates or closely resembles the characteristic style of another entity.
-
D.
isUrbanForm
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
E.
playsInStyleOf
Indicates that one entity performs, creates, or behaves in a manner characteristic of another entity’s style.
- F. None of above. chosen
Provenance (4 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_69f3495405b88190967af2157b43b896 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d6a482fc8190b526291cd99b8696 |
completed | May 3, 2026, 5:01 a.m. |
Created at: May 1, 2026, 1:25 a.m.