Triple
T19971441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourg at the Olympic Games |
E480084
|
entity |
| Predicate | hasWonOlympicGoldMedals |
P6616
|
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: [Luxembourg at the Olympic Games, hasWonOlympicGoldMedals, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonOlympicGoldMedals Context triple: [Luxembourg at the Olympic Games, hasWonOlympicGoldMedals, true]
-
A.
hasWonOlympicMedals
Indicates that the subject has earned one or more medals in Olympic Games competitions.
-
B.
olympicGoldMedals
chosen
Indicates that an entity has won one or more Olympic gold medals.
-
C.
olympicGoldWith
Indicates that the related entities won an Olympic gold medal together, typically as teammates in the same event or competition.
-
D.
OlympicGoldMedalistFor
Indicates that an entity has won a gold medal at the Olympic Games while representing a specified country, team, or organization.
-
E.
wonMedalAt
Indicates that an entity received a medal as a result of participating in a specific event or competition.
- 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_69e65bc9694881909a31841702ab9e5f |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.