Triple
T13424602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mound Township, Minnesota |
E313444
|
entity |
| Predicate | subdivisionName2 |
P766
|
FINISHED |
| Object |
Rock County
Rock County is a county in southwestern Minnesota known for its agricultural landscape and small rural communities.
|
E1073149
|
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: Rock County | Statement: [Mound Township, Minnesota, subdivisionName2, Rock County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rock County Context triple: [Mound Township, Minnesota, subdivisionName2, Rock County]
-
A.
Winnebago County
Winnebago County is a county in northern Illinois whose largest city and county seat is Rockford.
-
B.
Winnebago County
Winnebago County is a county in east-central Wisconsin that includes cities such as Oshkosh and Neenah along the western shore of Lake Winnebago.
-
C.
Vernon County
Vernon County is a county located in the western part of the U.S. state of Missouri, known for its largely rural character and the county seat of Nevada.
-
D.
Pike County
Pike County is a county in southeastern Alabama known for its agricultural economy and as the home of Troy University.
-
E.
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.
- 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: Rock County Triple: [Mound Township, Minnesota, subdivisionName2, Rock County]
Generated description
Rock County is a county in southwestern Minnesota known for its agricultural landscape and small rural communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rock County Target entity description: Rock County is a county in southwestern Minnesota known for its agricultural landscape and small rural communities.
-
A.
Winnebago County
Winnebago County is a county in northern Illinois whose largest city and county seat is Rockford.
-
B.
Winnebago County
Winnebago County is a county in east-central Wisconsin that includes cities such as Oshkosh and Neenah along the western shore of Lake Winnebago.
-
C.
Vernon County
Vernon County is a county located in the western part of the U.S. state of Missouri, known for its largely rural character and the county seat of Nevada.
-
D.
Pike County
Pike County is a county in southeastern Alabama known for its agricultural economy and as the home of Troy University.
-
E.
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.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed066408190a416880affd8416e |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac78104881909ea8d41cfb8d4574 |
completed | May 6, 2026, 9:02 p.m. |
| NEDg | Description generation | batch_69fbae186bb881908ea17ae6b12825af |
completed | May 6, 2026, 9:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbaebaab508190a609fa151c686a0d |
completed | May 6, 2026, 9:12 p.m. |
Created at: April 9, 2026, 9:39 p.m.