Triple
T8543379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 666 |
E202254
|
entity |
| Predicate | catalogNumberExample |
P8090
|
FINISHED |
| Object | Vertigo 6673 001 (original LP release) |
—
|
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: Vertigo 6673 001 (original LP release) | Statement: [666, catalogNumberExample, Vertigo 6673 001 (original LP release)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: catalogNumberExample Context triple: [666, catalogNumberExample, Vertigo 6673 001 (original LP release)]
-
A.
hasPartNumber
Indicates that one entity is assigned or associated with a specific part number used to identify it within a catalog, system, or inventory.
-
B.
categoryNumbering
Indicates that items within a category are assigned an ordered or structured numbering scheme that defines their position or sequence in that category.
-
C.
serialNumber
Indicates a unique identifying code assigned to an individual item or instance within a series or batch.
-
D.
catalogCode
chosen
Indicates that an entity is assigned a specific catalog identifier or code used for classification or reference.
-
E.
modelNumber
Indicates that one entity is the specific model identifier or code assigned to another entity (such as a product or device).
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6e381d4819084e230389a3ecb77 |
completed | March 31, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69cbd113e05c81908f4f3fc1b5925164 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:18 p.m.