Triple
T8184607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kusilvak Census Area |
E191150
|
entity |
| Predicate | primaryTransportationModes |
P44050
|
FINISHED |
| Object | small aircraft |
—
|
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: small aircraft | Statement: [Kusilvak Census Area, primaryTransportationModes, small aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTransportationModes Context triple: [Kusilvak Census Area, primaryTransportationModes, small aircraft]
-
A.
transportModeImportant
Indicates that the mode of transport used is considered significant or plays an important role in the context of the relationship or action.
-
B.
transportModeFamily
chosen
Indicates the general category or family of transportation mode to which a specific transport mode belongs (e.g., road, rail, air, water).
-
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.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
- 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_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c507f248190b599b4a629b7518a |
completed | March 31, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69cb36a7952481908f34e3e82f375a84 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:41 p.m.