Triple
T23548856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobermory 12 Year Old |
E577980
|
entity |
| Predicate | maturationCharacter |
P143545
|
FINISHED |
| Object | balanced oak maturation |
—
|
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: balanced oak maturation | Statement: [Tobermory 12 Year Old, maturationCharacter, balanced oak maturation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maturationCharacter Context triple: [Tobermory 12 Year Old, maturationCharacter, balanced oak maturation]
-
A.
maturationEffect
chosen
Indicates the influence or change that maturation (natural developmental progression over time) has on an entity’s characteristics, behavior, or state.
-
B.
maturationPractice
Indicates a process or set of actions that contribute to the development, refinement, or maturation of something over time.
-
C.
maturationTown
Indicates that an entity reaches maturity, develops fully, or undergoes its primary growth or coming-of-age process in a particular town.
-
D.
maturity
Indicates that an entity has reached a specified stage of development, completeness, or readiness, often marking the point at which certain rights, obligations, or behaviors become applicable.
-
E.
characterAgeDescriptor
Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
- 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aecd60a881908c257d9ba67080c8 |
completed | April 29, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:11 p.m.