Triple
T18685920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thompsonville, Michigan |
E456861
|
entity |
| Predicate | hasPrimaryTransportationType |
P70707
|
FINISHED |
| Object | road |
—
|
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: road | Statement: [Thompsonville, Michigan, hasPrimaryTransportationType, road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryTransportationType Context triple: [Thompsonville, Michigan, hasPrimaryTransportationType, road]
-
A.
hasPrimaryTransportationMode
chosen
Indicates the main or most frequently used mode of transportation associated with an entity.
-
B.
hasSecondaryTransportationMode
Indicates that an entity is associated with an additional, non-primary mode of transportation it can use or provide.
-
C.
hasTransportationAbove
Indicates that one entity provides or has transportation infrastructure or services located above another entity (e.g., elevated roads, railways, or transit lines).
-
D.
primaryTransportModel
Indicates that one transport model is designated as the main or default model used for a given context or entity.
-
E.
isTransportationType
Indicates that one entity functions as a mode or category of transportation for the other entity.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2c58188190b906c9ab080a76ff |
completed | April 19, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69e478db7a248190a8c6584673773923 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.