Triple
T5064419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manhattan, Kansas |
E114108
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Riley County |
E220974
|
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: Riley County | Statement: [Manhattan, Kansas, county, Riley County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Riley County Context triple: [Manhattan, Kansas, county, Riley County]
-
A.
Riley County, Kansas
chosen
Riley County, Kansas is a county in northeastern Kansas known for being home to the city of Manhattan and Kansas State University.
-
B.
Hutchinson County
Hutchinson County is a rural county in the Texas Panhandle known for its oil and gas production and small, closely knit communities.
-
C.
Webster County
Webster County is a rural county in southwestern Georgia known for its small population, agricultural landscape, and location within the state’s historic Black Belt region.
-
D.
Webster County
Webster County is a rural county in central West Virginia known for its mountainous terrain, outdoor recreation opportunities, and small, close-knit communities.
-
E.
Osage County, Kansas
Osage County, Kansas is a rural county in east-central Kansas known for its small communities, agricultural economy, and location within the Topeka metropolitan area.
- 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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd747756bc8190863c426e6fd6e8f7 |
completed | March 20, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfbd5d67c881909b57ead8968a840b |
completed | March 22, 2026, 9:58 a.m. |
Created at: March 20, 2026, 1:38 p.m.