Triple
T4508821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auxerrois |
E101998
|
entity |
| Predicate | commonOakUsage |
P11801
|
FINISHED |
| Object | often aged in 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: often aged in oak barrels | Statement: [Auxerrois, commonOakUsage, often aged in oak barrels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonOakUsage Context triple: [Auxerrois, commonOakUsage, often aged in oak barrels]
-
A.
oakAffinity
Indicates a special connection, preference, or strong association between an entity and oak (such as oak trees, wood, or oak-related environments).
-
B.
woodProperty
Indicates that one entity specifies or characterizes a property or attribute of wood associated with another entity.
-
C.
hasTrees
Indicates that something possesses or contains one or more trees.
-
D.
widelyUsedIn
chosen
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
E.
forestryActivity
Indicates activities related to the management, use, or cultivation of forest resources, such as logging, planting, or forest maintenance.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd570f9b1c8190b52ace855dbf6641 |
completed | March 20, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69bd5218afb4819087c99e0a1f22e137 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:01 p.m.