Triple
T20894397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Park, Iowa |
E514492
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Dixon County
Dixon County is a county-level administrative region in the U.S. state of Nebraska.
|
E1478236
|
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: Dixon County | Statement: [Lake Park, Iowa, locatedIn, Dixon County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dixon County Context triple: [Lake Park, Iowa, locatedIn, Dixon County]
-
A.
Noble County
Noble County is a rural county in southeastern Ohio known for its small communities, Appalachian landscape, and historical ties to the state’s early oil and gas industry.
-
B.
Morgan County
Morgan County is a rural county in northeastern Colorado known for its agricultural economy and small communities centered around the city of Fort Morgan.
-
C.
Morgan County
Morgan County is a rural county in the Eastern Panhandle of West Virginia, known for its mountainous terrain, outdoor recreation, and small-town communities.
-
D.
Morgan County
Morgan County is a county in central Indiana, United States, that forms part of the greater Indianapolis metropolitan region.
-
E.
Morgan County
Morgan County is a county in northern Alabama known for its seat in Decatur and its role in the Huntsville-Decatur metropolitan area.
- 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: Dixon County Triple: [Lake Park, Iowa, locatedIn, Dixon County]
Generated description
Dixon County is a county-level administrative region in the U.S. state of Nebraska.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dixon County Target entity description: Dixon County is a county-level administrative region in the U.S. state of Nebraska.
-
A.
Noble County
Noble County is a rural county in southeastern Ohio known for its small communities, Appalachian landscape, and historical ties to the state’s early oil and gas industry.
-
B.
Morgan County
Morgan County is a rural county in northeastern Colorado known for its agricultural economy and small communities centered around the city of Fort Morgan.
-
C.
Morgan County
Morgan County is a county in northern Alabama known for its seat in Decatur and its role in the Huntsville-Decatur metropolitan area.
-
D.
Morgan County
Morgan County is a rural county in northern Utah known for its mountainous terrain, outdoor recreation, and small-town communities northeast of Salt Lake City.
-
E.
Morgan County
Morgan County is a rural county in the Eastern Panhandle of West Virginia, known for its mountainous terrain, outdoor recreation, and small-town communities.
- 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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d06129788190b88ab807af4641c1 |
completed | April 21, 2026, 1:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09a5a2d128819081763172f6214e27 |
completed | May 17, 2026, 11:25 a.m. |
| NEDg | Description generation | batch_6a09a63fb6988190922458ad9e7b8a3a |
completed | May 17, 2026, 11:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09a696eabc8190936063b841039053 |
completed | May 17, 2026, 11:29 a.m. |
Created at: April 16, 2026, 12:46 p.m.