Triple
T21425008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greeny |
E528529
|
entity |
| Predicate | serialNumberStatus |
P89544
|
FINISHED |
| Object | original 1959 Gibson serial number |
—
|
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: original 1959 Gibson serial number | Statement: [Greeny, serialNumberStatus, original 1959 Gibson serial number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serialNumberStatus Context triple: [Greeny, serialNumberStatus, original 1959 Gibson serial number]
-
A.
serialNumber
Indicates a unique identifying code assigned to an individual item or instance within a series or batch.
-
B.
serialNumberColor
Indicates a relationship where a specific serial number is associated with a particular color.
-
C.
serviceNumberStatus
Indicates the current operational or availability state associated with a specific service number.
-
D.
serialNumberRange
Indicates that there is a specified range of serial numbers within which the related entities or items fall.
-
E.
numberingStatus
chosen
Indicates the status or condition of an entity’s assigned number or numbering process (e.g., whether it has been numbered, is pending, or has a particular numbering state).
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee813c7a048190a400e364c8df1dcf |
completed | April 26, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 5:48 p.m.