Triple
T21047821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordic skiing events at the 1952 Winter Olympics |
E518493
|
entity |
| Predicate | multiSportEventComponent |
P129671
|
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: [Nordic skiing events at the 1952 Winter Olympics, multiSportEventComponent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: multiSportEventComponent Context triple: [Nordic skiing events at the 1952 Winter Olympics, multiSportEventComponent, yes]
-
A.
multiSport
Indicates that an entity participates in, is associated with, or is designed for more than one sport.
-
B.
plannedMultiSportEvent
Indicates that an event has been organized to include multiple different sports or athletic disciplines as part of a coordinated program.
-
C.
partOfMultiSportEvent
chosen
Indicates that an event or competition is included as one component within a larger multi-sport event.
-
D.
sportsAttraction
Indicates a relationship where an entity serves as a venue, site, or draw specifically for sports-related activities or events.
-
E.
sportEventTypeOrganized
Indicates that an entity organizes or is responsible for arranging a specific type of sports event.
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcf5b01481909db49aa5be3846aa |
completed | April 21, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf6728881908a2a43a5c8804a2a |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:34 p.m.