Triple
T15077736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borden County |
E380048
|
entity |
| Predicate | isDryCounty |
P117227
|
FINISHED |
| Object | historically dry or partially dry |
—
|
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: historically dry or partially dry | Statement: [Borden County, isDryCounty, historically dry or partially dry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDryCounty Context triple: [Borden County, isDryCounty, historically dry or partially dry]
-
A.
isCornerCountyOf
Indicates that a county lies at or near the corner where two or more larger administrative regions (such as states or districts) meet.
-
B.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
C.
isDryCommunity
Indicates that a community prohibits or restricts the sale and/or consumption of alcoholic beverages.
-
D.
canDryOut
Indicates that one entity has the ability or tendency to cause another entity to lose moisture and become dry.
-
E.
wasCounty
Indicates that an entity previously held the status or role of a county in relation to a larger administrative or political unit.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7fe5a208190823900b25e298dab |
completed | April 15, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9645b9c8190a5712456dbd78029 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:03 a.m.