Triple
T30067159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 264 (Kentucky) |
E764064
|
entity |
| Predicate | isUrbanSegmentOf |
P80700
|
FINISHED |
| Object | Interstate Highway System in Kentucky |
—
|
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 Highway System in Kentucky | Statement: [Interstate 264 (Kentucky), isUrbanSegmentOf, Interstate Highway System in Kentucky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanSegmentOf Context triple: [Interstate 264 (Kentucky), isUrbanSegmentOf, Interstate Highway System in Kentucky]
-
A.
isUrbanSectionOf
chosen
Indicates that one area or segment is the part of a larger entity that lies within an urban or city environment.
-
B.
isUrbanRoute
Indicates that a route is located within, passes through, or primarily serves an urban or metropolitan area.
-
C.
urbanSegmentName
Indicates the specific name assigned to a segment within an urban area or city layout.
-
D.
isUrbanStreet
Indicates that a given street is located within an urban area or city environment rather than a rural or suburban setting.
-
E.
isSuburbanStreetOf
Indicates that one entity is a street located within or characteristic of the suburban area associated with another entity.
- 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_69f2247221388190a13a22c47094a0ef |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67ca767788190abd71ea33ce049e5 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 6:59 p.m.