Triple
T31807144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US 250 Bus. |
E811902
|
entity |
| Predicate | intersectionType |
P193422
|
FINISHED |
| Object | signalized intersections |
—
|
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: signalized intersections | Statement: [US 250 Bus., intersectionType, signalized intersections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intersectionType Context triple: [US 250 Bus., intersectionType, signalized intersections]
-
A.
intersectionRole
Indicates a role or function that an entity specifically holds at the point where two or more entities, paths, or sets intersect.
-
B.
fieldIntersection
Indicates that two or more fields or domains share a common overlapping area or set of elements.
-
C.
isIntersectionOf
Indicates that something is the exact common part shared by two or more other things, typically where they overlap or meet.
-
D.
intersectionPhysics
Indicates that two or more physical objects occupy overlapping space or come into contact according to physical simulation or geometric collision rules.
-
E.
servesIntersection
Indicates that one entity provides service or operational coverage to a specific road or transit intersection.
- 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_69f348e70d188190b4637c5509f81274 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd474b7e788190a9bb9b542d878f60 |
completed | May 8, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69fd46d8b2f0819099d92d72c902f60e |
completed | May 8, 2026, 2:13 a.m. |
| PDg | Predicate description generation | batch_69fd474a71648190b6b6ae4991db81b1 |
completed | May 8, 2026, 2:15 a.m. |
Created at: April 30, 2026, 11:43 p.m.