Triple
T5735128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salvator Mundi |
E126482
|
entity |
| Predicate | paddleNumberOfBuyer |
P66174
|
FINISHED |
| Object | bidding via phone |
—
|
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: bidding via phone | Statement: [Salvator Mundi, paddleNumberOfBuyer, bidding via phone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paddleNumberOfBuyer Context triple: [Salvator Mundi, paddleNumberOfBuyer, bidding via phone]
-
A.
numberOfOrders
Indicates the total count of orders associated with a given entity or context.
-
B.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
-
C.
canBePurchasedWith
Indicates that one entity is able to be bought or acquired using another entity as the form of payment.
-
D.
userCount
Indicates the number of users associated with or involved in a given context or entity.
-
E.
buyer
Indicates a relationship where one entity purchases or acquires goods, services, or rights from another entity in exchange for payment or compensation.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c6488881909bed4a4534d57f70 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c028fec2bc819083f5dca6a8d9d435 |
completed | March 22, 2026, 5:38 p.m. |
Created at: March 22, 2026, 3:47 p.m.