Triple
T6769090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Bannister |
E154997
|
entity |
| Predicate | olympicPlacement |
P73172
|
FINISHED |
| Object | fourth place in 1500 metres at 1952 Summer 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: fourth place in 1500 metres at 1952 Summer Olympics | Statement: [Roger Bannister, olympicPlacement, fourth place in 1500 metres at 1952 Summer Olympics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: olympicPlacement Context triple: [Roger Bannister, olympicPlacement, fourth place in 1500 metres at 1952 Summer Olympics]
-
A.
OlympicStatus
Indicates that an entity holds a particular status or role in relation to the Olympic Games (e.g., being an Olympic sport, event, athlete, or host).
-
B.
olympicGames
Indicates that an entity is an edition or instance of the Olympic Games event.
-
C.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
D.
medalistForCountry
Indicates that an entity is a medal-winning representative (medalist) competing on behalf of a specified country.
-
E.
OlympicMedal
Indicates that an entity has been awarded an Olympic medal in a specific event or discipline.
- F. None of above. chosen
Provenance (4 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d232d1f08190bc30c0f24f28c475 |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1d5f1908190989efc8a2d18c965 |
completed | March 27, 2026, 6:52 p.m. |
Created at: March 27, 2026, 2:12 p.m.