Triple
T2409975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-22 |
E50363
|
entity |
| Predicate | hasScenicOverlooks |
P9193
|
FINISHED |
| Object | Lake Michigan viewpoints |
—
|
LITERAL 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: Lake Michigan viewpoints | Statement: [M-22, hasScenicOverlooks, Lake Michigan viewpoints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScenicOverlooks Context triple: [M-22, hasScenicOverlooks, Lake Michigan viewpoints]
-
A.
hasScenicViewOf
chosen
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
B.
hasScenicSections
Indicates that a route, path, or area contains segments that are visually attractive or offer notable scenic views.
-
C.
hasMountainScenery
Indicates that a place or area features views or landscapes dominated by mountains.
-
D.
hasScenicDrive
Indicates that one entity offers or features a visually appealing or picturesque driving route associated with it.
-
E.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
- F. None of above.
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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:58 p.m.