Triple
T5227108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red, Hot and Blue |
E118016
|
entity |
| Predicate | workPeriodOfComposer |
P25964
|
FINISHED |
| Object | 1930s |
—
|
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: 1930s | Statement: [Red, Hot and Blue, workPeriodOfComposer, 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workPeriodOfComposer Context triple: [Red, Hot and Blue, workPeriodOfComposer, 1930s]
-
A.
notableWorkPeriod
chosen
Indicates the time span during which an entity produced or was associated with its most significant or well-known works.
-
B.
partOfComposerOeuvre
Indicates that a musical work belongs to and is included within the overall body of compositions created by a particular composer.
-
C.
workPeriod
Indicates the span of time during which an entity is engaged in a particular work or employment activity.
-
D.
hasMusicalComposer
Indicates that one entity serves as the musical composer responsible for creating the music associated with another entity.
-
E.
hasComposerInResidence
Indicates that an organization or institution has officially appointed a specific composer to serve in a resident or ongoing compositional role.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7addbdb88190baf9f47fc4cbb7fc |
completed | March 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69bd77bd2a448190a9ae5afd2585a7b9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:48 p.m.