Triple
T25341011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senna–Prost collision 1990 practice crash |
E635411
|
entity |
| Predicate | tookPlaceInCategory |
P158461
|
FINISHED |
| Object | Formula One practice session |
—
|
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: Formula One practice session | Statement: [Senna–Prost collision 1990 practice crash, tookPlaceInCategory, Formula One practice session]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookPlaceInCategory Context triple: [Senna–Prost collision 1990 practice crash, tookPlaceInCategory, Formula One practice session]
-
A.
tookPlaceInAdministrativeEntity
Indicates that an event or occurrence happened within the jurisdiction or boundaries of a specific administrative entity.
-
B.
takesPlace
Indicates that an event or action occurs or is situated at a particular time, place, or context.
-
C.
takesPlaceInRegion
Indicates that an event or occurrence happens within the boundaries of a specified geographic or administrative region.
-
D.
tookPlaceAtEvent
Indicates that an action or occurrence happened during or in the context of a specific event.
-
E.
tookPlaceFrom
Indicates that an event or occurrence started or was ongoing beginning at a specified time or location.
- 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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f498b6672881909d3257dc6b52caa3 |
completed | May 1, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 1:32 p.m.