Triple
T6453216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dodge City Community College |
E139924
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Ford County |
E580659
|
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: Ford County | Statement: [Dodge City Community College, county, Ford County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ford County Context triple: [Dodge City Community College, county, Ford County]
-
A.
Ford County
chosen
Ford County is a county in southwestern Kansas known for its historic cattle town Dodge City and its role in the American Old West.
-
B.
Cole County
Cole County was the former name of what is now Union County in the southeastern part of South Dakota.
-
C.
Ford County, Illinois
Ford County, Illinois is a predominantly rural county in east-central Illinois known for its agricultural landscape and small communities such as Paxton, its county seat.
-
D.
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.
-
E.
Butler County
Butler County is a rural county in south-central Alabama known for its pine forests, small towns, and location along the Interstate 65 corridor.
- 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_69c008b301948190a35854e5284dc822 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d1c7c481909df9d2369edf5e74 |
completed | March 22, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bd982208190bbf5f00a85f7098d |
completed | March 27, 2026, 9:20 a.m. |
Created at: March 22, 2026, 4:47 p.m.