Triple
T19955240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungary at the Olympic Games |
E479663
|
entity |
| Predicate | menWaterPoloOlympicTitles |
P6616
|
FINISHED |
| Object | multiple Olympic gold medals |
—
|
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: multiple Olympic gold medals | Statement: [Hungary at the Olympic Games, menWaterPoloOlympicTitles, multiple Olympic gold medals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: menWaterPoloOlympicTitles Context triple: [Hungary at the Olympic Games, menWaterPoloOlympicTitles, multiple Olympic gold medals]
-
A.
wonOlympicFootballTournament
Indicates that an entity secured first place in the Olympic football (soccer) tournament in a given edition of the Olympic Games.
-
B.
worldCupWinsInDiscipline
Indicates the number of times an entity has won a World Cup in a specific discipline or category.
-
C.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
D.
worldChampionshipsGoldMedal
Indicates that the subject has won a gold medal at a world championship competition.
-
E.
olympicGoldMedals
chosen
Indicates that an entity has won one or more Olympic gold medals.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65aefd9488190b8cdfa8543db8d31 |
completed | April 20, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.