Triple
T219971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troup County |
E4190
|
entity |
| Predicate | hasSeat |
P3522
|
FINISHED |
| Object | LaGrange |
E30624
|
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: LaGrange | Statement: [Troup County, hasSeat, LaGrange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LaGrange Context triple: [Troup County, hasSeat, LaGrange]
-
A.
LaGrange
LaGrange is a town in Dutchess County, New York, known as a suburban community in the Hudson Valley region.
-
B.
LaGrange
chosen
LaGrange is a small city in western Georgia known for its historic downtown, proximity to West Point Lake, and role as an economic and cultural center for the surrounding region.
-
C.
Greenville, Georgia
Greenville, Georgia is a small city in west-central Georgia that serves as the administrative and civic center of Meriwether County.
-
D.
Carrollton
Carrollton is a suburban city in the Dallas–Fort Worth metropolitan area known for its residential communities, business parks, and convenient access to major highways.
-
E.
Fayetteville, Georgia
Fayetteville, Georgia is a suburban city south of Atlanta that serves as the county seat of Fayette County and is known for its historic downtown and proximity to major film production studios.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c6d0fa08190810139b14f4851bc |
completed | Feb. 28, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a386137da0819090249faf5127a5be |
completed | March 1, 2026, 12:19 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.