Triple
T30020706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shizuka Arakawa |
E762727
|
entity |
| Predicate | World Championships medal |
P51904
|
FINISHED |
| Object | gold |
—
|
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: gold | Statement: [Shizuka Arakawa, World Championships medal, gold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: World Championships medal Context triple: [Shizuka Arakawa, World Championships medal, gold]
-
A.
worldChampionshipMedalAtEvent
Indicates that an entity has won a medal in a world championship at a specified event.
-
B.
worldChampionshipsGoldMedal
chosen
Indicates that the subject has won a gold medal at a world championship competition.
-
C.
worldChampionshipMedalInDiscipline
Indicates that an entity has won a medal in a specific discipline at a world championship event.
-
D.
Four Continents Championships medal
Indicates that an entity has been awarded a medal at the Four Continents Figure Skating Championships.
-
E.
worldChampionshipBronzeMedals
Indicates the number of bronze medals an entity has earned at world championship 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_69f2246ee6e48190b69e837b913b398a |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
Created at: April 29, 2026, 6:47 p.m.