Triple
T13665178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Killington Resort |
E327097
|
entity |
| Predicate | WorldCupDiscipline |
P111056
|
FINISHED |
| Object | women's slalom |
—
|
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: women's slalom | Statement: [Killington Resort, WorldCupDiscipline, women's slalom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldCupDiscipline Context triple: [Killington Resort, WorldCupDiscipline, women's slalom]
-
A.
WorldCupDisciplineTitles
Indicates the number or types of discipline-specific titles an entity has won at the World Cup.
-
B.
WorldChampionshipsDiscipline
Indicates the specific discipline or event category in which a world championship competition is held or a title is contested.
-
C.
hasOlympicDiscipline
Indicates that an entity (typically a sport) includes or is associated with a specific discipline as recognized in the Olympic Games.
-
D.
esportDiscipline
Indicates that one entity is a specific esports game or discipline in which the other entity participates or is involved.
-
E.
worldCupWinsInDiscipline
Indicates the number of times an entity has won a World Cup in a specific discipline or category.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc623fcc88190bbad97541c040b7a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.