Triple
T32268858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Calle & His Latin Jazz Ensemble: Mamblue |
E824362
|
entity |
| Predicate | featuresSection |
P38807
|
FINISHED |
| Object | horn section |
—
|
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: horn section | Statement: [Ed Calle & His Latin Jazz Ensemble: Mamblue, featuresSection, horn section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSection Context triple: [Ed Calle & His Latin Jazz Ensemble: Mamblue, featuresSection, horn section]
-
A.
featuresStringSection
Indicates that an entity includes or is associated with a specific section of text represented as a string.
-
B.
section1Feature
Indicates that something is a feature, characteristic, or component specifically associated with section 1.
-
C.
featuresIntroductionOf
Indicates that one entity includes or presents the introduction or opening section created by another entity.
-
D.
featuresHero
Indicates that something (such as a work, product, or story) prominently includes or centers around a particular hero as a main character or focus.
-
E.
featuresSegment
chosen
Indicates that one entity includes or highlights a particular segment or portion of another entity as a notable part of it.
- 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_69f3490e73588190915f282edd105772 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a00c486d394819084fe93d5bb11ea1e |
completed | May 10, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_6a00c39d99d48190a94bfa057213499c |
completed | May 10, 2026, 5:42 p.m. |
Created at: May 1, 2026, 12:42 a.m.