Triple
T7565760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shayba Arena |
E178907
|
entity |
| Predicate | hasOlympicSportDiscipline |
P50990
|
FINISHED |
| Object | men's ice hockey |
—
|
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 ice hockey | Statement: [Shayba Arena, hasOlympicSportDiscipline, men's ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOlympicSportDiscipline Context triple: [Shayba Arena, hasOlympicSportDiscipline, men's ice hockey]
-
A.
hasOlympicDiscipline
chosen
Indicates that an entity (typically a sport) includes or is associated with a specific discipline as recognized in the Olympic Games.
-
B.
competedInDiscipline
Indicates that an entity took part in a competition or event within a specific discipline or category.
-
C.
OlympicGoldMedalSport
Indicates that the subject sport is one in which the object athlete or team has won an Olympic gold medal.
-
D.
OlympicStatus
Indicates that an entity holds a particular status or role in relation to the Olympic Games (e.g., being an Olympic sport, event, athlete, or host).
-
E.
hasOlympicFunction
Indicates that an entity serves a specific role, duty, or function within the context of the Olympic Games or Olympic movement.
- 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_69c69f2f80288190b95cceb4da92ab2b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8fde87c81909795fc713d7378ff |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4dc485c819080da13e3b7f4f08f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:50 p.m.