Triple
T18356705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parlophone PMC 1206 (mono) |
E439814
|
entity |
| Predicate | labelDesign |
P45253
|
FINISHED |
| Object | Parlophone black and yellow label |
—
|
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: Parlophone black and yellow label | Statement: [Parlophone PMC 1206 (mono), labelDesign, Parlophone black and yellow label]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelDesign Context triple: [Parlophone PMC 1206 (mono), labelDesign, Parlophone black and yellow label]
-
A.
labelOf
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
-
B.
labelDepicts
Indicates that one entity serves as a label or caption that visually or textually represents, illustrates, or describes another entity.
-
C.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
-
D.
maskDesigner
Indicates that one entity is the designer or creator of a particular mask associated with another entity.
-
E.
frontDesign
chosen
Indicates that one entity serves as the primary or visible front-facing design or appearance of another entity.
- 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e516d776cc8190937d7e1d42a36a3b |
completed | April 19, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e44fed3fdc81908f4ed6a81db42416 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:37 a.m.