Triple
T19566488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1948 Winter Olympics |
E489594
|
entity |
| Predicate | firstGoldMedalistForCountry |
P45222
|
FINISHED |
| Object | Gretchen Fraser for the United States in alpine skiing |
—
|
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: Gretchen Fraser for the United States in alpine skiing | Statement: [1948 Winter Olympics, firstGoldMedalistForCountry, Gretchen Fraser for the United States in alpine skiing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstGoldMedalistForCountry Context triple: [1948 Winter Olympics, firstGoldMedalistForCountry, Gretchen Fraser for the United States in alpine skiing]
-
A.
goldMedalistNationality
Indicates the nationality of the athlete who won the gold medal in a given event or competition.
-
B.
firstOlympicsInCountry
Indicates that the referenced Olympic Games were the first edition ever hosted in the specified country.
-
C.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
D.
olympicDebut
Indicates the event or year in which an entity first participated in the Olympic Games.
-
E.
medalistForCountry
chosen
Indicates that an entity is a medal-winning representative (medalist) competing on behalf of a specified country.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f784ff88190a515c78429de3caf |
completed | April 20, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:42 p.m.