Triple
T16108534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limestone County, Alabama |
E390806
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | Limestone County |
E178140
|
NE 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: Limestone County | Statement: [Limestone County, Alabama, abbreviation, Limestone County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limestone County Context triple: [Limestone County, Alabama, abbreviation, Limestone County]
-
A.
Limestone County
chosen
Limestone County is a county in northern Alabama known for its mix of agricultural communities, growing suburban areas, and proximity to the Huntsville metropolitan region.
-
B.
Greenwood County
Greenwood County is a county in western South Carolina known for its mix of small-city life, manufacturing, and agricultural communities centered around the city of Greenwood.
-
C.
Kingfisher County
Kingfisher County is a rural county in central Oklahoma known for its agricultural economy and small-town communities.
-
D.
Lamar County
Lamar County is a rural county in western Alabama known for its small communities and agricultural landscape.
-
E.
Lamar County
Lamar County is a county in northeastern Texas known for its seat in the city of Paris and its location near the Oklahoma border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20165aa9c81908c5358cca2b0d0fe |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b274fa3481908b019036cd2ae627 |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5 a.m.