Triple
T29282441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hatful of Hollow |
E742416
|
entity |
| Predicate | originalLabelCatalogueNumber |
P34455
|
FINISHED |
| Object | Rough Trade ROUGH 76 |
—
|
NE NERFINISHED |
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: Rough Trade ROUGH 76 | Statement: [Hatful of Hollow, originalLabelCatalogueNumber, Rough Trade ROUGH 76]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLabelCatalogueNumber Context triple: [Hatful of Hollow, originalLabelCatalogueNumber, Rough Trade ROUGH 76]
-
A.
originalCatalogNumberFor
Indicates that one resource is the original catalog number assigned to another resource.
-
B.
recordLabelCatalogNumber
chosen
Indicates the catalog or identification number assigned to a release by a record label.
-
C.
keyCatalogueNumber
Indicates the catalog or reference number assigned to a key within a key collection or inventory system.
-
D.
originalLabel
Indicates the primary or initial label or name originally assigned to an entity before any changes or translations.
-
E.
hasCatalogueNumberInDeutschCatalogue
Indicates that an entity is assigned a specific catalogue number within the Deutsch catalogue classification system.
- 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_69f09121ed8c8190b4cb27be3619c262 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: April 28, 2026, 12:55 p.m.