Triple
T15842225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Circuit de Barcelona-Catalunya |
E384126
|
entity |
| Predicate | startFinishStraightLengthM |
P30560
|
FINISHED |
| Object | 1047 |
—
|
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: 1047 | Statement: [Circuit de Barcelona-Catalunya, startFinishStraightLengthM, 1047]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startFinishStraightLengthM Context triple: [Circuit de Barcelona-Catalunya, startFinishStraightLengthM, 1047]
-
A.
hasStartFinishStraight
Indicates that something includes a straight segment that serves as both the starting and finishing section of a course or track.
-
B.
mainStraightLengthM
chosen
Indicates the length, measured in meters, of the main straight segment (typically of a track, road, or similar linear feature).
-
C.
mainStraightLengthKm
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
D.
hasMainStraightLengthKm
Indicates the length in kilometers of the primary or main straight segment associated with an entity.
-
E.
hasStraightCourseDistance
Indicates that a route or path has a specified distance measured along its straight, unobstructed course.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e88ff08190a1035269e8fdaa6a |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.