Triple
T24971214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porsche Carrera Cup Germany |
E624893
|
entity |
| Predicate | typicalCalendarSize |
P180111
|
FINISHED |
| Object | 6–8 race weekends per season |
—
|
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: 6–8 race weekends per season | Statement: [Porsche Carrera Cup Germany, typicalCalendarSize, 6–8 race weekends per season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCalendarSize Context triple: [Porsche Carrera Cup Germany, typicalCalendarSize, 6–8 race weekends per season]
-
A.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
B.
typicalPackSize
Indicates the usual quantity of items contained together in a single package for that entity.
-
C.
typicalCastSize
Indicates the usual or standard number of cast members involved in a production or performance.
-
D.
typicalPanelSize
Indicates the usual or standard dimensions associated with a given panel.
-
E.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
- 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_69e2ff24512481908e9a72315b8d0354 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
| PDg | Predicate description generation | batch_69f73221eef88190bd8905e6e9f5a586 |
completed | May 3, 2026, 11:31 a.m. |
Created at: April 18, 2026, 6:01 a.m.