Triple
T3200011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manzanilla sherry |
E67026
|
entity |
| Predicate | agingSystem |
P31167
|
FINISHED |
| Object | solera system |
—
|
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: solera system | Statement: [Manzanilla sherry, agingSystem, solera system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agingSystem Context triple: [Manzanilla sherry, agingSystem, solera system]
-
A.
careerSystem
Indicates a relationship where an entity is part of, governed by, or operates within a particular career-related system or framework.
-
B.
agingMethod
chosen
Indicates the process or technique by which something (typically a product or material) is matured, aged, or allowed to develop its characteristics over time.
-
C.
agingPotential
Indicates the capacity or suitability of something to improve, develop, or remain effective over time as it ages.
-
D.
boarding
Indicates that one entity is getting onto or entering a vehicle, vessel, or similar conveyance associated with another entity.
-
E.
trainingSystem
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9ad4b1c8190bc6ad0f025f238c8 |
completed | March 8, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69ad9e05e4f48190adbe4366cdba2349 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.