Triple
T9167169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porsche 911 GT2 RS |
E219988
|
entity |
| Predicate | NürburgringLapTime |
P77656
|
FINISHED |
| Object | 6:47.3 (approximate, 2017) |
—
|
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: 6:47.3 (approximate, 2017) | Statement: [Porsche 911 GT2 RS, NürburgringLapTime, 6:47.3 (approximate, 2017)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NürburgringLapTime Context triple: [Porsche 911 GT2 RS, NürburgringLapTime, 6:47.3 (approximate, 2017)]
-
A.
fastestLapTime
chosen
Indicates the shortest recorded time an entity achieved to complete a single lap in a given context or event.
-
B.
safetyCarLapRecordHolder
Indicates that one entity holds the record for the most notable or fastest performance during a lap completed under safety car conditions in a race.
-
C.
racingNumber
Indicates that an entity has been assigned a specific competition or race identification number used to distinguish it from other participants.
-
D.
fastestLapLapNumber
Indicates the specific lap number on which the fastest lap was achieved in a race.
-
E.
trackDesigner
Indicates that one entity is the designer or creator responsible for the layout or structure of a track associated with 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaade47cc81909b5c127dc8aa1340 |
completed | April 1, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69cc6605c6808190a30d92da006206ac |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:22 p.m.