Triple
T5006986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winneshiek Medical Center |
E112520
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Decorah |
E338597
|
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: Decorah | Statement: [Winneshiek Medical Center, city, Decorah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Decorah Context triple: [Winneshiek Medical Center, city, Decorah]
-
A.
Decorah
chosen
Decorah is a small city in northeastern Iowa known for its scenic bluffs, Norwegian-American heritage, and as the home of Luther College.
-
B.
Orono
Orono is a suburban city in Minnesota known for its affluent residential communities and scenic location along the north shore of Lake Minnetonka.
-
C.
Orono
Orono is a small rural village in Ontario, Canada, known for its historic downtown, agricultural surroundings, and community events.
-
D.
Houghton
Houghton is a wealthy, historically significant suburb of Johannesburg, South Africa, known for being the longtime home of Nelson Mandela.
-
E.
Houghton
Houghton is a residential and waterfront neighborhood in the city of Kirkland, Washington, known for its parks, lake access, and small-town feel within the greater Seattle 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd72e8a0308190a47d81943ad85bba |
completed | March 20, 2026, 4:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9261ef088190a012d55294b9e3c2 |
completed | March 21, 2026, 12:43 p.m. |
Created at: March 20, 2026, 1:35 p.m.