Triple
T13227627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benz Patent-Motorwagen |
E314921
|
entity |
| Predicate | distanceOfFamousJourney |
P16230
|
FINISHED |
| Object | about 106 km |
—
|
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: about 106 km | Statement: [Benz Patent-Motorwagen, distanceOfFamousJourney, about 106 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceOfFamousJourney Context triple: [Benz Patent-Motorwagen, distanceOfFamousJourney, about 106 km]
-
A.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
B.
distanceFromAlexandria_km
Indicates the distance, measured in kilometers, between a given location and Alexandria.
-
C.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
D.
distanceFromGizaPlateau
Indicates the measured spatial distance between a given location and the Giza Plateau.
-
E.
distanceTraveled
chosen
Indicates the total length of the path an entity has moved over a period of time or between two points.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:21 p.m.