Triple
T31542159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Evers-Swindell |
E804773
|
entity |
| Predicate | hasWonMultipleOlympicGolds |
P173078
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Caroline Evers-Swindell, hasWonMultipleOlympicGolds, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonMultipleOlympicGolds Context triple: [Caroline Evers-Swindell, hasWonMultipleOlympicGolds, true]
-
A.
hasWonOlympicMedals
Indicates that the subject has earned one or more medals in Olympic Games competitions.
-
B.
isMultipleOlympicChampion
chosen
Indicates that an entity has won Olympic championship titles in more than one edition of the Olympic Games.
-
C.
olympicGoldWith
Indicates that the related entities won an Olympic gold medal together, typically as teammates in the same event or competition.
-
D.
isOlympicMedalistIn
Indicates that an individual has won at least one Olympic medal in a specified sport or event.
-
E.
olympicGoldMedalist
Indicates that an entity has won a gold medal at the Olympic Games.
- 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_69f348d11a048190a65eb8384a3754ac |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
Created at: April 30, 2026, 10:06 p.m.