Triple
T8147692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spain Olympic football team |
E190254
|
entity |
| Predicate | medalTallyOlympicFootball |
P6616
|
FINISHED |
| Object | 1 gold medal |
—
|
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: 1 gold medal | Statement: [Spain Olympic football team, medalTallyOlympicFootball, 1 gold medal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medalTallyOlympicFootball Context triple: [Spain Olympic football team, medalTallyOlympicFootball, 1 gold medal]
-
A.
wonOlympicFootballTournament
Indicates that an entity secured first place in the Olympic football (soccer) tournament in a given edition of the Olympic Games.
-
B.
olympicFootballAppearances
Indicates the number of times an entity has participated in Olympic football (soccer) tournaments.
-
C.
WorldCupMedal
Indicates that an entity has received a medal (e.g., gold, silver, bronze) for its performance in a FIFA World Cup tournament.
-
D.
olympicGoldMedals
chosen
Indicates that an entity has won one or more Olympic gold medals.
-
E.
totalOlympicMedals
Indicates the total number of Olympic medals an entity has earned across all Games and events.
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb447e74e081908df774edb2134209 |
completed | March 31, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cb369c0d0481908762c488d7f77e74 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:36 p.m.