Triple
T2208332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French autoroute network |
E50854
|
entity |
| Predicate | hasTollFreeSections |
P31367
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [French autoroute network, hasTollFreeSections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTollFreeSections Context triple: [French autoroute network, hasTollFreeSections, yes]
-
A.
hasToll
Indicates that the use, access, or passage associated with something requires payment of a toll or fee.
-
B.
hasTollVariant
Indicates that an entity has a version or instance that requires paying a toll or fee for use or access.
-
C.
hasTollSegment
Indicates that a route, road, or path includes a segment where a toll must be paid.
-
D.
isFreeOfCharge
chosen
Indicates that no payment or fee is required for the associated action, service, or item.
-
E.
isTollFacilityOf
Indicates that a facility (such as a toll booth, plaza, or gantry) is part of, or used to collect tolls for, a specific toll road or toll transportation infrastructure.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.