Triple
T35753219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Grand Prix |
E1033370
|
entity |
| Predicate | hasHostedTitleDecidingRaces |
P195611
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [German Grand Prix, hasHostedTitleDecidingRaces, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHostedTitleDecidingRaces Context triple: [German Grand Prix, hasHostedTitleDecidingRaces, yes]
-
A.
hasHostedDryRaces
Indicates that an entity has organized or held races in which the track conditions were dry (i.e., not wet or rainy).
-
B.
hasHostedSport
Indicates that a place or organization has served as the venue or organizer for one or more sporting events.
-
C.
hasHeldRacesInCity
Indicates that an entity has organized or conducted races that took place within a particular city.
-
D.
hasBeenHostOf
Indicates that an entity has previously served in the role of host for another entity, such as an event, show, or program.
-
E.
hasHostedWetRaces
Indicates that the subject has previously hosted races that took place under wet conditions (e.g., rain or a wet track).
- 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69fddac42c4081908568649058e86458 |
completed | May 8, 2026, 12:44 p.m. |
Created at: May 3, 2026, 4:06 p.m.