Triple
T191789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rust Belt |
E3736
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Milwaukee |
E10031
|
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: Milwaukee | Statement: [Rust Belt, hasMajorCity, Milwaukee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Milwaukee Context triple: [Rust Belt, hasMajorCity, Milwaukee]
-
A.
Milwaukee
chosen
Milwaukee is the largest city in Wisconsin, known for its brewing traditions, industrial history, and location on the western shore of Lake Michigan.
-
B.
Green Bay, Wisconsin
Green Bay, Wisconsin is a city in northeastern Wisconsin best known as the home of the NFL’s Green Bay Packers and one of the oldest continuously operating professional football franchises in the United States.
-
C.
Duluth
Duluth is a major port city in northeastern Minnesota known for its shipping industry, scenic Lake Superior shoreline, and role as a regional transportation hub.
-
D.
Delano
Delano is the middle name of Franklin D. Roosevelt, the 32nd president of the United States.
-
E.
Madison, Wisconsin, United States
Madison, Wisconsin, United States is the capital city of Wisconsin, known for its major research university, vibrant cultural scene, and numerous lakes.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a259669ba08190a5be1d2e10e70b27 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a32bc5d56c8190bbe922eee86bcc58 |
completed | Feb. 28, 2026, 5:54 p.m. |
Created at: Feb. 28, 2026, 2:41 a.m.