Triple
T22852372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2013 World Figure Skating Championships |
E566385
|
entity |
| Predicate | hasFreeSkateSegment |
P149966
|
FINISHED |
| Object | men's free skate |
—
|
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: men's free skate | Statement: [2013 World Figure Skating Championships, hasFreeSkateSegment, men's free skate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFreeSkateSegment Context triple: [2013 World Figure Skating Championships, hasFreeSkateSegment, men's free skate]
-
A.
freeSkateDuration
Indicates the length of time allocated or used for a free skate segment in a skating performance or competition.
-
B.
personalBestFreeSkateEvent
Indicates the event in which an individual achieved their highest personal score in the free skate discipline.
-
C.
isFreeToAttend
Indicates that attending the event or activity does not require any payment or admission fee.
-
D.
hasSkateSharpening
Indicates that an entity offers or provides skate sharpening services to others.
-
E.
hasFreeZone
Indicates that an entity includes or is associated with a designated free zone area where special rules, privileges, or exemptions apply.
- 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_69e2458750b481908a8e4cf4609cc6cf |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17eb9a5b8819091cbb4ac42fbf778 |
completed | April 29, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69eed2d507c08190895ed971af0fc755 |
completed | April 27, 2026, 3:07 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:36 p.m.