Triple
T27025307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-59 |
E680767
|
entity |
| Predicate | roadTypeSegment |
P1019
|
FINISHED |
| Object | divided highway in some sections |
—
|
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: divided highway in some sections | Statement: [M-59, roadTypeSegment, divided highway in some sections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadTypeSegment Context triple: [M-59, roadTypeSegment, divided highway in some sections]
-
A.
roadType
chosen
Indicates the classification or category of a road based on its functional or physical characteristics.
-
B.
roadTypeAtSquare
Indicates the specific type or classification of road present at a given square or location in a spatial grid or map.
-
C.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
D.
roadNumberType
Indicates the classification or type category assigned to a road’s identifying number (e.g., highway, route, local road).
-
E.
highwaySegment
Indicates a road section that forms part of a larger highway route.
- 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_69eeeb5450988190bfc9a3c012ac463a |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6223131b0819081deea3d5ed98ea5 |
completed | May 2, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 7:10 a.m.