Triple
T6033341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massillon, Ohio |
E134359
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Stark County |
E551475
|
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: Stark County | Statement: [Massillon, Ohio, county, Stark County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stark County Context triple: [Massillon, Ohio, county, Stark County]
-
A.
Stark County
chosen
Stark County is a county in northeastern Ohio known for its seat in Canton and its role in the region’s industrial and political history.
-
B.
Pike County
Pike County is a county in southeastern Alabama known for its agricultural economy and as the home of Troy University.
-
C.
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.
-
D.
Pike County
Pike County is a rural county in northeastern Pennsylvania known for its forests, rivers, and location along the Delaware River near the New York and New Jersey borders.
-
E.
Warren County
Warren County is a largely rural county in northwestern New Jersey known for its small towns, farmland, and role as a residential area for commuters in the New York metropolitan region.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b220608190b156be95632cf3b3 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11cf60d00819084bc8405595f7989 |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:08 p.m.