Triple
T15527605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribera del Duero DO |
E369121
|
entity |
| Predicate | agingVesselCommon |
P26083
|
FINISHED |
| Object | oak barrels |
—
|
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: oak barrels | Statement: [Ribera del Duero DO, agingVesselCommon, oak barrels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agingVesselCommon Context triple: [Ribera del Duero DO, agingVesselCommon, oak barrels]
-
A.
hasVessel
chosen
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
-
B.
vesselService
Indicates a service relationship in which one entity provides, operates, or maintains a vessel (such as a ship or boat) for another entity.
-
C.
featuresVessel
Indicates that one entity includes, presents, or prominently displays a particular vessel as part of its composition, content, or configuration.
-
D.
namedVesselOf
Indicates that one entity is the specific named vessel (e.g., ship, boat, or craft) associated with or belonging to another entity.
-
E.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0414620588190958ffde651ccab5f |
completed | April 16, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_69ded28ab0588190a47a9090d1238707 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 4:05 a.m.