Triple
T22911876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A&M 31454 0526 2 |
E568616
|
entity |
| Predicate | partOfLabelCatalog |
P134425
|
FINISHED |
| Object | A&M Records catalog |
—
|
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: A&M Records catalog | Statement: [A&M 31454 0526 2, partOfLabelCatalog, A&M Records catalog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfLabelCatalog Context triple: [A&M 31454 0526 2, partOfLabelCatalog, A&M Records catalog]
-
A.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
-
B.
labelCatalogType
Indicates that an entity is assigned a specific catalog type label, defining its classification within a cataloging system.
-
C.
catalogPartOf
chosen
Indicates that one catalog item is a component, section, or subset of a larger catalog or cataloged collection.
-
D.
labelOf
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
-
E.
categoryLabel_H
Indicates that an entity is assigned a human-readable category label or classification.
- 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_69e2458cd9e48190943ad2e34485d939 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18075a0048190bd150e2badeeb7c2 |
completed | April 29, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:42 p.m.