Triple
T9573672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biathlon at the 2002 Winter Olympics |
E230988
|
entity |
| Predicate | hasMedalEvents |
P89884
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Biathlon at the 2002 Winter Olympics, hasMedalEvents, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedalEvents Context triple: [Biathlon at the 2002 Winter Olympics, hasMedalEvents, yes]
-
A.
medalEventsFor
Indicates a relationship where one entity lists or specifies the medal-awarding events associated with another entity.
-
B.
numberOfMedalEvents
Indicates the total count of distinct medal-awarding events associated with a given context (such as a sport, competition, or edition of games).
-
C.
hasMedalCount
Indicates the relationship between an entity and the number of medals it possesses or has been awarded.
-
D.
wonMedalAt
Indicates that an entity received a medal as a result of participating in a specific event or competition.
-
E.
includesMedal
Indicates that an entity’s set, collection, or record contains or features a particular medal as one of its elements.
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99a94c788190a4bb5d2b676908ac |
completed | April 1, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:05 p.m.