Triple
T18267794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cotter Schools |
E437529
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Winona |
—
|
NE NERFINISHED |
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: Winona | Statement: [Cotter Schools, city, Winona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Winona Context triple: [Cotter Schools, city, Winona]
-
A.
Winona
chosen
Winona is a historic river city in southeastern Minnesota known for its Mississippi River bluffs, cultural festivals, and regional educational institutions.
-
B.
Willemina
Willemina is a feminine given name of Dutch origin, historically borne by figures such as Willemina Jacoba van Gogh, the sister of painter Vincent van Gogh.
-
C.
Lyonne
Lyonne is the surname of American actress, writer, director, and producer Natasha Lyonne, known for her roles in "Orange Is the New Black" and "Russian Doll."
-
D.
Carola
Carola is a Dutch politician known for serving as Deputy Prime Minister and Minister of Agriculture, Nature and Food Quality in the Netherlands.
-
E.
Carola
Carola is a feminine given name used in various European languages, often considered a variant of Caroline or Carol.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7bda5c8190a5a85f3cfb7aa4ef |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.