Triple
T22929087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County Route 500-series network |
E569386
|
entity |
| Predicate | routeNumberRange |
P49979
|
FINISHED |
| Object | 500–599 |
—
|
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: 500–599 | Statement: [County Route 500-series network, routeNumberRange, 500–599]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeNumberRange Context triple: [County Route 500-series network, routeNumberRange, 500–599]
-
A.
roadNumberRange
chosen
Indicates that a road is identified by a continuous range of road numbers between a specified minimum and maximum.
-
B.
RVNumberRange
Indicates that a recreational vehicle’s number or identifier falls within a specified numeric range.
-
C.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
D.
zoneNumberRange
Indicates that there is an associated range of zone numbers, typically specifying the minimum and maximum zone identifiers applicable in a given context.
-
E.
serialNumberRange
Indicates that there is a specified range of serial numbers within which the related entities or items fall.
- 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_69e2458f7d008190901dccbaebeaba24 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180dc33e8819099e5ad87207de57f |
completed | April 29, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:44 p.m.