Triple
T13288342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Panorama Circuit |
E316498
|
entity |
| Predicate | hasLapRecordCategory |
P109333
|
FINISHED |
| Object | Supercars |
—
|
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: Supercars | Statement: [Mount Panorama Circuit, hasLapRecordCategory, Supercars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLapRecordCategory Context triple: [Mount Panorama Circuit, hasLapRecordCategory, Supercars]
-
A.
F1LapRecordCategory
Indicates that an entity holds or pertains to a specific category of Formula 1 lap record (such as overall, qualifying, or race lap records).
-
B.
hasWorldRecordCategory
Indicates that an entity holding a world record is associated with a specific category or type of record.
-
C.
hasCompetitionCategory
Indicates that an entity is associated with a specific category or division within a competition.
-
D.
hasRankCategory
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
E.
hasRankingCategory
Indicates that an entity is associated with a particular ranking category or tier within an ordered classification system.
- F. None of above. chosen
Provenance (4 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:27 p.m.