Triple
T10942229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quebec Autoroute 40 |
E258500
|
entity |
| Predicate | hasServiceAreaAlong |
P13639
|
FINISHED |
| Object | rest areas and service stations |
—
|
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: rest areas and service stations | Statement: [Quebec Autoroute 40, hasServiceAreaAlong, rest areas and service stations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceAreaAlong Context triple: [Quebec Autoroute 40, hasServiceAreaAlong, rest areas and service stations]
-
A.
hasServiceAreas
chosen
Indicates that an entity provides services within, or is operational across, specific geographic or functional areas.
-
B.
hasPrimaryServiceArea
Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
-
C.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
D.
areaServedType
Indicates the type or category of area that is served by an entity or service.
-
E.
serviceAreaName
Indicates the designated name of the geographic or functional area that a service covers or operates within.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c33a7c8190b3347944f68ee431 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.