Triple
T6238267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northeastern Ohio |
E139529
|
entity |
| Predicate | containsCounty |
P5971
|
FINISHED |
| Object |
Richland County
Richland County is a county in north-central Ohio known for its mix of small cities, rural communities, and historical sites.
|
E593857
|
NE FINISHED |
How this triple was built (4 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: Richland County | Statement: [Northeastern Ohio, containsCounty, Richland County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richland County Context triple: [Northeastern Ohio, containsCounty, Richland County]
-
A.
Mason County
Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
-
B.
Harrison County
Harrison County is a rural county in western Iowa known for its agricultural landscape, small communities, and location along the Missouri River.
-
C.
Harrison County
Harrison County is a coastal county in southern Mississippi known for its tourism, casinos, and the cities of Biloxi and Gulfport.
-
D.
Rich County
Rich County is a sparsely populated rural county in northeastern Utah, known for its ranching communities and proximity to Bear Lake.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Richland County Triple: [Northeastern Ohio, containsCounty, Richland County]
Generated description
Richland County is a county in north-central Ohio known for its mix of small cities, rural communities, and historical sites.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Richland County Target entity description: Richland County is a county in north-central Ohio known for its mix of small cities, rural communities, and historical sites.
-
A.
Mason County
Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
-
B.
Harrison County
Harrison County is a rural county in western Iowa known for its agricultural landscape, small communities, and location along the Missouri River.
-
C.
Harrison County
Harrison County is a coastal county in southern Mississippi known for its tourism, casinos, and the cities of Biloxi and Gulfport.
-
D.
Rich County
Rich County is a sparsely populated rural county in northeastern Utah, known for its ranching communities and proximity to Bear Lake.
-
E.
Pike County
Pike County is a county in southeastern Alabama known for its agricultural economy and as the home of Troy University.
- F. None of above. chosen
Provenance (5 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0630373088190a9d4b1f7e442c129 |
completed | March 22, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64ba0968c819091fae910b8c82879 |
completed | March 27, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_69c64c5e5e5c8190b24aea7e4114daa5 |
completed | March 27, 2026, 9:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c64da81a0881908fc5716aeb0e47fa |
completed | March 27, 2026, 9:28 a.m. |
Created at: March 22, 2026, 4:23 p.m.