Triple
T35209394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Lions |
E1016630
|
entity |
| Predicate | WorldChampionshipMedalType |
P194816
|
FINISHED |
| Object | silver |
—
|
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: silver | Statement: [Lady Lions, WorldChampionshipMedalType, silver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldChampionshipMedalType Context triple: [Lady Lions, WorldChampionshipMedalType, silver]
-
A.
typeOfMedalEvent
Indicates the specific medal category (e.g., gold, silver, bronze) associated with a particular event.
-
B.
medalType
Indicates the specific category or class of a medal associated with an award or achievement.
-
C.
worldChampionshipMedalColor
chosen
Indicates the color of a medal that an entity received in a world championship event.
-
D.
typeOfMedalist
Indicates the specific category or rank of medal (e.g., gold, silver, bronze) associated with a given medalist.
-
E.
WorldChampionshipMedalsTotal
Indicates the total number of medals an entity has won 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_69f76ddf549c8190869d0af076fd2c28 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
Created at: May 3, 2026, 4:02 p.m.