Triple
T17759747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barren County, Kentucky |
E443337
|
entity |
| Predicate | isDryOrMoistCounty |
P117227
|
FINISHED |
| Object | moist (partially dry) county |
—
|
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: moist (partially dry) county | Statement: [Barren County, Kentucky, isDryOrMoistCounty, moist (partially dry) county]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDryOrMoistCounty Context triple: [Barren County, Kentucky, isDryOrMoistCounty, moist (partially dry) county]
-
A.
isDryCounty
chosen
Indicates that a county prohibits or significantly restricts the sale of alcoholic beverages.
-
B.
isDryCommunity
Indicates that a community prohibits or restricts the sale and/or consumption of alcoholic beverages.
-
C.
hasDrySeasonCause
Indicates that one factor or condition is the underlying cause of a location or region experiencing a dry season.
-
D.
canDryOut
Indicates that one entity has the ability or tendency to cause another entity to lose moisture and become dry.
-
E.
isCornerCountyOf
Indicates that a county lies at or near the corner where two or more larger administrative regions (such as states or districts) meet.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48421c3048190b26864b72aad0d70 |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:10 a.m.