Triple
T37334913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapio Mäkelä |
E926863
|
entity |
| Predicate | medalTypeInEvent |
P26560
|
FINISHED |
| Object | gold medal in 4 × 10 km relay at the 1952 Winter Olympics |
—
|
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 medal in 4 × 10 km relay at the 1952 Winter Olympics | Statement: [Tapio Mäkelä, medalTypeInEvent, gold medal in 4 × 10 km relay at the 1952 Winter Olympics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medalTypeInEvent Context triple: [Tapio Mäkelä, medalTypeInEvent, gold medal in 4 × 10 km relay at the 1952 Winter Olympics]
-
A.
typeOfMedalEvent
Indicates the specific medal category (e.g., gold, silver, bronze) associated with a particular event.
-
B.
medalType
chosen
Indicates the specific category or class of a medal associated with an award or achievement.
-
C.
medalEventsFor
Indicates a relationship where one entity lists or specifies the medal-awarding events associated with another entity.
-
D.
medalTypesAwarded
Indicates the specific types or categories of medals that have been awarded in a given awarding event or context.
-
E.
medalSport
Indicates that a medal was awarded in a particular sport or sporting discipline.
- 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_69f76eb4e8a881908bd40da28f36fc7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb8c38a9688190be524246f5682107 |
completed | May 6, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9c6e0481908565bd849e869b24 |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.