Triple
T25301287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Korea women's national handball team |
E634349
|
entity |
| Predicate | medalsAtOlympicGames |
P136233
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [South Korea women's national handball team, medalsAtOlympicGames, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medalsAtOlympicGames Context triple: [South Korea women's national handball team, medalsAtOlympicGames, multiple]
-
A.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
B.
OlympicMedal
Indicates that an entity has been awarded an Olympic medal in a specific event or discipline.
-
C.
totalOlympicMedals
Indicates the total number of Olympic medals an entity has earned across all Games and events.
-
D.
hasWonOlympicMedals
chosen
Indicates that the subject has earned one or more medals in Olympic Games competitions.
-
E.
athleticsGoldMedals
Indicates that the subject has won one or more gold medals in athletics competitions.
- 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_69e75a972c6481909bc11710e8d30a6c |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48fd8461c81908e461c9809bbfdbf |
completed | May 1, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 1:24 p.m.