Triple
T22805356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olympic Games handball tournament |
E564515
|
entity |
| Predicate | medalSignificance |
P149788
|
FINISHED |
| Object | Olympic champion title |
—
|
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: Olympic champion title | Statement: [Olympic Games handball tournament, medalSignificance, Olympic champion title]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medalSignificance Context triple: [Olympic Games handball tournament, medalSignificance, Olympic champion title]
-
A.
medalFor
Indicates that a medal is awarded to an entity in recognition of a specific achievement, action, or service.
-
B.
medalIn
Indicates that an entity has received a medal or award in a particular event, field, or competition.
-
C.
medalSport
Indicates that a medal was awarded in a particular sport or sporting discipline.
-
D.
medalType
Indicates the specific category or class of a medal associated with an award or achievement.
-
E.
medalName
Indicates the specific name or title of a medal associated with an entity.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d5b37cc8190a41d8f304ba8d609 |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:31 p.m.