Triple
T23862086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takin' Off |
E592475
|
entity |
| Predicate | followsInLabelCatalog |
P125022
|
FINISHED |
| Object | Blue Note Records releases of early 1960s |
—
|
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: Blue Note Records releases of early 1960s | Statement: [Takin' Off, followsInLabelCatalog, Blue Note Records releases of early 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsInLabelCatalog Context triple: [Takin' Off, followsInLabelCatalog, Blue Note Records releases of early 1960s]
-
A.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
-
B.
followsInName
Indicates that one entity’s name is derived from, modeled after, or intentionally patterned to follow the naming of another entity.
-
C.
belongsToCatalogOf
Indicates that one item is included within, or is a member of, a particular catalog or collection.
-
D.
followsIn
chosen
Indicates that one entity comes after or succeeds another in a sequence, order, or progression.
-
E.
hasLabel
Indicates that an entity is associated with a specific textual label or name used to identify or describe it.
- 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_69e25d22eb488190914b193aff952e83 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cae0b4bc819089f491d9e817d160 |
completed | April 29, 2026, 9:09 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:13 p.m.