Triple
T799957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upson County |
E17106
|
entity |
| Predicate | formedFrom |
P402
|
FINISHED |
| Object | Crawford County |
E50673
|
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: Crawford County | Statement: [Upson County, formedFrom, Crawford County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crawford County Context triple: [Upson County, formedFrom, Crawford County]
-
A.
Crawford County
chosen
Crawford County is a rural county in central Georgia known for its agricultural landscape and small-town communities west of Macon.
-
B.
Pike County
Pike County is a county in west-central Georgia, United States, known for its rural character and location within the Atlanta metropolitan area’s broader region.
-
C.
Greene County
Greene County is a rural county in eastern New York State known for encompassing a significant portion of the scenic Catskill Mountains.
-
D.
Greene County
Greene County is a rural county in southwestern Pennsylvania known for its Appalachian landscape, coal mining history, and small-town communities within the greater Pittsburgh region.
-
E.
Butler County
Butler County is a county in western Pennsylvania, north of Pittsburgh, known for its mix of suburban communities, rural landscapes, and growing industrial and service sectors.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7cb26dc8190bdd3a278b8695873 |
completed | March 1, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e56e7fc8190a81cbd97e20fd0e6 |
completed | March 8, 2026, 5:51 a.m. |
Created at: March 1, 2026, 7:38 p.m.