Triple
T35574843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cäcilie Bertha Ringer |
E1028046
|
entity |
| Predicate | madeJourneyWithVehicle |
P98191
|
FINISHED |
| Object | Benz Patent-Motorwagen |
—
|
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: Benz Patent-Motorwagen | Statement: [Cäcilie Bertha Ringer, madeJourneyWithVehicle, Benz Patent-Motorwagen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: madeJourneyWithVehicle Context triple: [Cäcilie Bertha Ringer, madeJourneyWithVehicle, Benz Patent-Motorwagen]
-
A.
travelsInVehicle
Indicates that an entity is moving from one place to another while being transported inside or on a vehicle.
-
B.
drivenTo
Indicates that one entity causes or compels another entity to move or act toward a particular state, goal, or location.
-
C.
droveFor
Indicates that one entity operated a vehicle on behalf of, or in service to, another entity for a certain period or purpose.
-
D.
hasRideExperience
chosen
Indicates that one entity has undergone, participated in, or possesses experience with a particular ride or riding activity in relation to another entity.
-
E.
usedAsVehicleFor
Indicates that one entity functions as a means of transportation or conveyance for 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_69f76e0386688190b931bacdc145938c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.