Triple
T6061224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuna Kim |
E135035
|
entity |
| Predicate | wonSilverMedalInEvent |
P15191
|
FINISHED |
| Object | ladies' singles |
—
|
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: ladies' singles | Statement: [Yuna Kim, wonSilverMedalInEvent, ladies' singles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonSilverMedalInEvent Context triple: [Yuna Kim, wonSilverMedalInEvent, ladies' singles]
-
A.
wonMedalAt
Indicates that an entity received a medal as a result of participating in a specific event or competition.
-
B.
silverMedalist
chosen
Indicates that an entity finished in second place in a competition or event, earning the silver medal.
-
C.
olympicGoldMedalInEvent
Indicates that an entity has won an Olympic gold medal in a specified sporting event.
-
D.
bronzeMedalist
Indicates that an entity finished third in a competition or event, earning the bronze medal.
-
E.
worldChampionshipSilverMedals
Indicates that the subject has won one or more silver medals at a world championship 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0571fcecc8190a68e0d0668bbbfa7 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049f031408190b08b2766237c5dd0 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.