Triple
T13590723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hennessy |
E324684
|
entity |
| Predicate | hasMasterBlender |
P110190
|
FINISHED |
| Object | cellar master |
—
|
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: cellar master | Statement: [Hennessy, hasMasterBlender, cellar master]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMasterBlender Context triple: [Hennessy, hasMasterBlender, cellar master]
-
A.
masteredBy
Indicates that a subject (such as a skill, topic, or resource) has been fully learned, controlled, or become highly proficiently used by a particular agent or entity.
-
B.
hasBalletMaster
Indicates that an entity is associated with or overseen by a specific ballet master responsible for its ballet-related training, direction, or instruction.
-
C.
hasSculptor
Indicates that one entity serves as the sculptor (creator of a sculpture) of another entity.
-
D.
hasFlightMaster
Indicates that an entity provides or is associated with a flight master service or function for another entity.
-
E.
masterPainter
Indicates that one entity is recognized as a highly skilled, authoritative painter in relation to another or within a given context.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.