Triple
T16243655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Kegonsa State Park |
E394313
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Madison, Wisconsin |
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, Wisconsin | Statement: [Lake Kegonsa State Park, locatedNear, Madison, Wisconsin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madison, Wisconsin Context triple: [Lake Kegonsa State Park, locatedNear, Madison, Wisconsin]
-
A.
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.
-
B.
Washington, Wisconsin
Washington, Wisconsin is a small town located in Eau Claire County in the western part of the U.S. state of Wisconsin.
-
C.
Madison
Madison is a suburban city in northern Alabama known for its proximity to Huntsville and its strong schools and residential communities.
-
D.
Madison
Madison is a coastal town in south-central Connecticut known for its beaches, historic New England charm, and popular Hammonasset Beach State Park.
-
E.
Madison
Madison is the codename for a later-generation Itanium processor variant developed by Intel for high-end server and enterprise computing.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24560060c8190ace4f4c0bd0d886d |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f8ae4288190b59e4af3e3d95000 |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:04 a.m.