Triple
T34412565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel E.H. Taylor Jr. Bourbon |
E883312
|
entity |
| Predicate | bottlingControlRequirement |
P179390
|
FINISHED |
| Object | U.S. government supervision |
—
|
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: U.S. government supervision | Statement: [Colonel E.H. Taylor Jr. Bourbon, bottlingControlRequirement, U.S. government supervision]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bottlingControlRequirement Context triple: [Colonel E.H. Taylor Jr. Bourbon, bottlingControlRequirement, U.S. government supervision]
-
A.
bottlingProof
Indicates the specific alcohol proof at which a beverage is bottled.
-
B.
bottlingType
Indicates the specific method or style in which a liquid product is bottled or packaged.
-
C.
bottlingOnSite
Indicates that the bottling of a product takes place at the same physical location where it is produced or processed.
-
D.
bottlingMaterial
Indicates the material from which a container or bottle used for holding a product is made.
-
E.
bottlingFrequency
Indicates how often a bottling process or event occurs over a given period.
- 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_69f349c2e3b88190a67834eb5bcffeaf |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f720cc1bfc8190a16118e3af8e9316 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71fb0172c81908f23e95ff16b0dec |
completed | May 3, 2026, 10:13 a.m. |
Created at: May 1, 2026, 1:59 a.m.