Triple
T28739357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unified Team Olympic figure skating team |
E730895
|
entity |
| Predicate | wonMedalsIn |
P44482
|
FINISHED |
| Object | figure skating at the 1992 Winter Olympics |
—
|
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: figure skating at the 1992 Winter Olympics | Statement: [Unified Team Olympic figure skating team, wonMedalsIn, figure skating at the 1992 Winter Olympics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonMedalsIn Context triple: [Unified Team Olympic figure skating team, wonMedalsIn, figure skating at the 1992 Winter Olympics]
-
A.
wonMedalAt
chosen
Indicates that an entity received a medal as a result of participating in a specific event or competition.
-
B.
hasWonOlympicMedals
Indicates that the subject has earned one or more medals in Olympic Games competitions.
-
C.
medalsAttributedTo
Indicates that certain medals or awards are formally assigned or credited to a particular entity (such as a person, team, or organization).
-
D.
OlympicMedal
Indicates that an entity has been awarded an Olympic medal in a specific event or discipline.
-
E.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
- 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_69f043eae0908190b28ce314686247d7 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f657b2b1808190a9f7c80eef2efa99 |
completed | May 2, 2026, 7:59 p.m. |
| PD | Predicate disambiguation | batch_69f651ada6048190a7b4a6981565dc3a |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 6:02 a.m.