Triple
T32088990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waverly, Ohio |
E819531
|
entity |
| Predicate | hasNotableTransportation |
P87177
|
FINISHED |
| Object | U.S. Route 23 |
—
|
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: U.S. Route 23 | Statement: [Waverly, Ohio, hasNotableTransportation, U.S. Route 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableTransportation Context triple: [Waverly, Ohio, hasNotableTransportation, U.S. Route 23]
-
A.
notPublicTransit
Indicates that the transportation mode or route is not classified as public transit (e.g., it is private, restricted, or otherwise not available as general public transportation).
-
B.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
-
C.
hasTransportationSystem
Indicates that an entity possesses, operates, or is served by an organized system for transporting people or goods.
-
D.
hasNoMajorRideVehicles
Indicates that the subject lacks any primary or significant ride vehicles associated with it.
-
E.
hasTransportationElement
chosen
Indicates that one entity includes, involves, or is associated with a specific transportation-related component or feature.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a00dc330b148190aaae2ac6a5327960 |
completed | May 10, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_6a00d9d2904881909dafbfe7b9e5ad81 |
completed | May 10, 2026, 7:17 p.m. |
Created at: May 1, 2026, 12:25 a.m.