Triple
T14313582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minnesota–South Dakota border |
E354895
|
entity |
| Predicate | hasTransportationCrossings |
P113928
|
FINISHED |
| Object | highways |
—
|
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: highways | Statement: [Minnesota–South Dakota border, hasTransportationCrossings, highways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportationCrossings Context triple: [Minnesota–South Dakota border, hasTransportationCrossings, highways]
-
A.
hasBridgeCrossings
Indicates that one entity has one or more bridge structures that span across or connect over another entity (such as a road, river, or area).
-
B.
hasCrosswalks
Indicates that designated pedestrian crosswalks are present at or associated with the specified location or roadway segment.
-
C.
hasMajorCrossing
Indicates that one entity has a significant or primary intersection or crossing with another entity.
-
D.
hasBridgeTypeCrossing
Indicates that a bridge is characterized by a specific type of crossing it provides or supports.
-
E.
hasBayCrossing
Indicates that one place is connected to another by a crossing over a bay, such as a bridge, tunnel, or ferry route.
- F. None of above. chosen
Provenance (4 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b49e5481909b9ffab2d922e284 |
completed | April 14, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e9ded24819099200349cf80e068 |
completed | April 14, 2026, 12:10 p.m. |
Created at: April 10, 2026, 1:12 a.m.