Triple
T33787756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Note 1500/4000 series |
E865838
|
entity |
| Predicate | labelCatalogRange |
P177690
|
FINISHED |
| Object | 1500 series |
—
|
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: 1500 series | Statement: [Blue Note 1500/4000 series, labelCatalogRange, 1500 series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelCatalogRange Context triple: [Blue Note 1500/4000 series, labelCatalogRange, 1500 series]
-
A.
categoryRange
Indicates that a category or classification spans from a defined lower bound to an upper bound within a specified range.
-
B.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
-
C.
labelCatalogType
Indicates that an entity is assigned a specific catalog type label, defining its classification within a cataloging system.
-
D.
hasRangeCategory
Indicates that a property or measurement falls within a specified category or interval of possible values.
-
E.
allegedRangeCategory
Indicates that one entity is claimed or suspected to fall within a particular range category defined by another entity or classification.
- 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_69f3498ecc2c8190bcd85e3f11dc215e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: May 1, 2026, 1:45 a.m.