Triple
T7202236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Escambia County, Alabama |
E168774
|
entity |
| Predicate | hasBorderCounty |
P44905
|
FINISHED |
| Object | Conecuh County, Alabama |
—
|
NE NERFINISHED |
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: Conecuh County, Alabama | Statement: [Escambia County, Alabama, hasBorderCounty, Conecuh County, Alabama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderCounty Context triple: [Escambia County, Alabama, hasBorderCounty, Conecuh County, Alabama]
-
A.
hasNearbyCounty
chosen
Indicates that one county is geographically close to or directly adjacent to another county.
-
B.
bordersCountryViaCounty
Indicates that one country shares a border with another country specifically through a county-level administrative region.
-
C.
isCornerCountyOf
Indicates that a county lies at or near the corner where two or more larger administrative regions (such as states or districts) meet.
-
D.
locatedNearStateBorderWith
Indicates that one entity is situated geographically close to the border of a specified state.
-
E.
hasBorderCity
Indicates that one location is a city situated on or very near the border of another geographic or political region.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e94a9ee4819086de79fcdfa1836a |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:52 p.m.