Triple
T28107297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hockenheimring modern layout |
E710397
|
entity |
| Predicate | mainStraightLength_km |
P30559
|
FINISHED |
| Object | 0.65 |
—
|
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: 0.65 | Statement: [Hockenheimring modern layout, mainStraightLength_km, 0.65]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainStraightLength_km Context triple: [Hockenheimring modern layout, mainStraightLength_km, 0.65]
-
A.
mainStraightLengthKm
chosen
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
B.
mainStraightLengthM
Indicates the length, measured in meters, of the main straight segment (typically of a track, road, or similar linear feature).
-
C.
hasMainStraightLengthKm
Indicates the length in kilometers of the primary or main straight segment associated with an entity.
-
D.
roadLength
Indicates the measured distance or extent of a road, typically expressed in units of length.
-
E.
mainLayoutLengthKm
Indicates the length, measured in kilometers, of the primary or main layout 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_69ef9b71fdb081908b4a61cd7ff147c1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1c555081908787dbf76147f180 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 27, 2026, 9:09 p.m.