Triple
T7847989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southeastern Wisconsin |
E181969
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Cudahy |
E296699
|
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: Cudahy | Statement: [Southeastern Wisconsin, hasMajorCity, Cudahy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cudahy Context triple: [Southeastern Wisconsin, hasMajorCity, Cudahy]
-
A.
Cudahy
Cudahy is a small, densely populated city in southeastern Los Angeles County, California, known for its predominantly Latino community and urban residential character.
-
B.
Bayfield
Bayfield is a residential suburb of the historic town of Chepstow in Monmouthshire, Wales.
-
C.
Muskego
Muskego is a suburban city in Waukesha County, Wisconsin, known for its residential communities and numerous lakes and parks.
-
D.
Kaukauna, Wisconsin
Kaukauna, Wisconsin is a small industrial city on the Fox River known historically for its paper mills and hydroelectric power.
-
E.
City of Cudahy
chosen
The City of Cudahy is a small industrial and residential suburb located just south of Milwaukee in southeastern Wisconsin.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18e7f5988190808ae4dcfbc06991 |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccec5f00b48190b35f7cab67e7e5f9 |
completed | April 1, 2026, 9:58 a.m. |
Created at: March 30, 2026, 4:49 p.m.