Triple
T31984888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthias Mayer |
E816693
|
entity |
| Predicate | isMultipleOlympicChampion |
P173078
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Matthias Mayer, isMultipleOlympicChampion, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMultipleOlympicChampion Context triple: [Matthias Mayer, isMultipleOlympicChampion, true]
-
A.
olympicChampionIn
Indicates that an entity has won a championship title in a specified Olympic sport or event.
-
B.
isOlympicMedalistIn
Indicates that an individual has won at least one Olympic medal in a specified sport or event.
-
C.
hasWonOlympicMedals
Indicates that the subject has earned one or more medals in Olympic Games competitions.
-
D.
olympicGoldWith
Indicates that the related entities won an Olympic gold medal together, typically as teammates in the same event or competition.
-
E.
hasWonMultipleChampionships
Indicates that the subject has secured championship titles on more than one separate occasion.
- 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_69f348f6a3008190bfb59ca695fd68e2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b3ae2cb481909c375799c0ec5c07 |
completed | May 3, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: May 1, 2026, 12:12 a.m.