Triple
T22206107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy in London |
E548809
|
entity |
| Predicate | featuresArrangementStyle |
P96816
|
FINISHED |
| Object | pop arrangements |
—
|
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: pop arrangements | Statement: [Nancy in London, featuresArrangementStyle, pop arrangements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresArrangementStyle Context triple: [Nancy in London, featuresArrangementStyle, pop arrangements]
-
A.
featuresArrangementBy
Indicates that one entity determines or specifies the spatial or structural arrangement of features in another entity.
-
B.
featuresStringArrangementBy
Indicates that something presents or includes a specific arrangement or ordering of strings that is determined or provided by a particular agent or source.
-
C.
arrangementFeatures
Indicates that one entity specifies or characterizes the structural or compositional features of an arrangement involving another entity.
-
D.
containsArrangementsStyle
chosen
Indicates that one entity includes or features musical arrangements characterized by a particular style or stylistic approach.
-
E.
arrangementType
Indicates the specific kind or category of arrangement that characterizes how the related entities are organized or structured in relation to each other.
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b2868d88190af313b862fe9d8f2 |
completed | April 28, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e71b4dcc408190a30429fb08fcf39e |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:36 p.m.