Triple
T11145851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand under-23 national football team |
E263666
|
entity |
| Predicate | olympicFootballDiscipline |
P50990
|
FINISHED |
| Object | men's football |
—
|
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 football | Statement: [New Zealand under-23 national football team, olympicFootballDiscipline, men's football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: olympicFootballDiscipline Context triple: [New Zealand under-23 national football team, olympicFootballDiscipline, men's football]
-
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.
esportDiscipline
Indicates that one entity is a specific esports game or discipline in which the other entity participates or is involved.
-
C.
WorldCupDisciplineTitles
Indicates the number or types of discipline-specific titles an entity has won at the World Cup.
-
D.
olympicGames
Indicates that an entity is an edition or instance of the Olympic Games event.
-
E.
OlympicGoldMedalSport
Indicates that the subject sport is one in which the object athlete or team has won an Olympic gold medal.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e86e9ef48190b4df4b14319a954f |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.