Triple
T19971005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgium at the Olympic Games |
E480072
|
entity |
| Predicate | hasWonMedalsIn |
P89884
|
FINISHED |
| Object | athletics |
—
|
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: athletics | Statement: [Belgium at the Olympic Games, hasWonMedalsIn, athletics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonMedalsIn Context triple: [Belgium at the Olympic Games, hasWonMedalsIn, athletics]
-
A.
wonMedalAt
Indicates that an entity received a medal as a result of participating in a specific event or competition.
-
B.
hasWonOlympicMedals
Indicates that the subject has earned one or more medals in Olympic Games competitions.
-
C.
hasMedalEvents
chosen
Indicates that an entity has associated events in which medals are or can be awarded.
-
D.
hasMedalCount
Indicates the relationship between an entity and the number of medals it possesses or has been awarded.
-
E.
medalsAttributedTo
Indicates that certain medals or awards are formally assigned or credited to a particular entity (such as a person, team, or organization).
- 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.