Triple
T6026059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenduskeag, Maine |
E134183
|
entity |
| Predicate | primaryTransportation |
P46040
|
FINISHED |
| Object | local roads |
—
|
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: local roads | Statement: [Kenduskeag, Maine, primaryTransportation, local roads]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTransportation Context triple: [Kenduskeag, Maine, primaryTransportation, local roads]
-
A.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
-
B.
primaryTransport
chosen
Indicates that one entity serves as the main or most commonly used means of transportation for another entity.
-
C.
primaryTransportModel
Indicates that one transport model is designated as the main or default model used for a given context or entity.
-
D.
transportationContext
Indicates the situational or environmental conditions under which transportation occurs, such as mode, purpose, or circumstances of travel.
-
E.
usedTransportationInfrastructure
Indicates that an entity made use of some form of transportation infrastructure (such as roads, railways, or ports) to enable movement or transit.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04fc08c5c819085afab5b18bce4d1 |
completed | March 22, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69c049e75b3881908be106fbcf8c68d4 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:07 p.m.