Triple
T34174051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1927 Schneider Trophy |
E876618
|
entity |
| Predicate | totalRaceDistance |
P134622
|
FINISHED |
| Object | 350 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: 350 km | Statement: [1927 Schneider Trophy, totalRaceDistance, 350 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalRaceDistance Context triple: [1927 Schneider Trophy, totalRaceDistance, 350 km]
-
A.
distancePerRace
chosen
Indicates the total distance covered in a single race event or instance.
-
B.
raceDistanceType
Indicates the specific type or category of distance over which a race is conducted.
-
C.
majorRaceDistance
Indicates the standard or primary distance over which a major race or competition is contested.
-
D.
raceDistanceApprox
Indicates that the distance of a race is approximately equal to a specified value, allowing for some margin of error rather than requiring an exact match.
-
E.
typicalRaceDistanceUnit
Indicates the standard unit of measurement used to express the usual race distance associated with an 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_69f349ad97ac8190bf1f17417c970e64 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 1, 2026, 1:54 a.m.