Triple
T20693267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imaginary Landscape No. 4 |
E508602
|
entity |
| Predicate | performanceVariable |
P141112
|
FINISHED |
| Object | radio station selection |
—
|
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: radio station selection | Statement: [Imaginary Landscape No. 4, performanceVariable, radio station selection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performanceVariable Context triple: [Imaginary Landscape No. 4, performanceVariable, radio station selection]
-
A.
performanceWith
Indicates a relationship where two or more entities participate together in the same performance or staged presentation.
-
B.
performanceBasis
Indicates that one entity’s performance is evaluated, determined, or justified on the basis of another specified factor, standard, or reference.
-
C.
performanceUse
Indicates that something is used, employed, or utilized in the course of performing an action, task, or function.
-
D.
performance
Indicates that one entity’s effectiveness, quality, or success in carrying out a task, function, or role is being evaluated or characterized in relation to some standard or expectation.
-
E.
performanceModel
Indicates a relationship where one entity serves as a performance model that represents, predicts, or characterizes the performance behavior of another entity.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10fc4088190ab71ef078600954b |
completed | April 21, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c044d1108190b2b5d25de23f6401 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:09 p.m.