Triple
T636216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisconsin |
E16627
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Madison |
E11896
|
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: Madison | Statement: [Wisconsin, capital, Madison]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madison Context triple: [Wisconsin, capital, Madison]
-
A.
Madison
Madison is a common English surname and given name, historically associated with U.S. President James Madison and now widely used as a first name, especially for girls.
-
B.
Monroe
Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
-
C.
Madison, Wisconsin, United States
chosen
Madison, Wisconsin, United States is the capital city of Wisconsin, known for its major research university, vibrant cultural scene, and numerous lakes.
-
D.
Fort Madison
Fort Madison is a historic riverfront city in southeastern Iowa known for its Mississippi River port, 19th-century military fort heritage, and role as a regional transportation hub.
-
E.
Milwaukee
Milwaukee is the largest city in Wisconsin, known for its brewing traditions, industrial history, and location on the western shore of Lake Michigan.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee667f08190a0332b8f6c569e1a |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5dc91ff30819095a00852c3e2dfae |
completed | March 2, 2026, 6:53 p.m. |
Created at: March 1, 2026, 7:35 p.m.