Triple
T28551238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian Sportswoman of the Year |
E722889
|
entity |
| Predicate | dominantSportAmongWinners |
P132231
|
FINISHED |
| Object | alpine skiing |
—
|
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: alpine skiing | Statement: [Austrian Sportswoman of the Year, dominantSportAmongWinners, alpine skiing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dominantSportAmongWinners Context triple: [Austrian Sportswoman of the Year, dominantSportAmongWinners, alpine skiing]
-
A.
dominantSports
chosen
Indicates that a particular sport is the primary or most influential sport associated with an entity (such as a person, team, or region).
-
B.
fieldOfWinners
Indicates that a given field or domain is associated with the winners of a particular competition, award, or event.
-
C.
primarySport
Indicates the main sport with which an entity (such as a person, team, or organization) is most closely associated or primarily involved.
-
D.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
E.
languageOfMostWinners
Indicates the language in which the greatest number of winners (e.g., of an award or competition) are associated or have produced their work.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6cee45590819086e489bfccbe4ac3 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 28, 2026, 3:42 a.m.