Triple
T15752379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisconsin Highway 42 |
E381877
|
entity |
| Predicate | connectsToHighwayAtSouthernTerminus |
P22217
|
FINISHED |
| Object | Interstate 43 |
—
|
NE NERFINISHED |
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: Interstate 43 | Statement: [Wisconsin Highway 42, connectsToHighwayAtSouthernTerminus, Interstate 43]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToHighwayAtSouthernTerminus Context triple: [Wisconsin Highway 42, connectsToHighwayAtSouthernTerminus, Interstate 43]
-
A.
connectsToHighway
Indicates that one location, road, or route has a direct access point or linkage to a highway.
-
B.
hasSouthernTerminus
Indicates that one entity serves as the southern endpoint or terminus of another entity, such as a route, line, or path.
-
C.
roadTerminusOf
chosen
Indicates that a road ends at, or has its terminal point at, the referenced location or route.
-
D.
isSouthernmostHighwayCrossingOf
Indicates that one location is the furthest-south point at which a particular highway crosses a specified geographic feature or boundary.
-
E.
hasRoadTerminus
Indicates that one location or road segment serves as an endpoint or terminus for a particular road.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.