Triple
T37347860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sainte-Florine |
E927230
|
entity |
| Predicate | drivingLicenceIssuingAuthority |
P108937
|
FINISHED |
| Object | French state |
—
|
NE NERFINISHED |
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: French state | Statement: [Sainte-Florine, drivingLicenceIssuingAuthority, French state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingLicenceIssuingAuthority Context triple: [Sainte-Florine, drivingLicenceIssuingAuthority, French state]
-
A.
vehicleRegistrationAuthority
Indicates the authority or organization responsible for officially registering a vehicle and maintaining its registration records.
-
B.
licenceAuthority
chosen
Indicates that one entity has the official power or jurisdiction to grant, issue, or regulate licences for another entity or activity.
-
C.
countryOfLicence
Indicates the country that has issued or granted a particular licence.
-
D.
cityOfLicense
Indicates the city in which an entity (typically a broadcast station or similar regulated service) is officially licensed or authorized to operate.
-
E.
designationAuthority
Indicates the entity that has the official power or responsibility to assign, grant, or confer a particular designation to another 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_69f76eb5e034819088e53ab5b7909a68 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:16 p.m.