Triple
T28342489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Pulido |
E717851
|
entity |
| Predicate | hasOlympicParticipation |
P7486
|
FINISHED |
| Object | football at the Olympic Games |
—
|
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: football at the Olympic Games | Statement: [Alan Pulido, hasOlympicParticipation, football at the Olympic Games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOlympicParticipation Context triple: [Alan Pulido, hasOlympicParticipation, football at the Olympic Games]
-
A.
OlympicGamesParticipated
chosen
Indicates that an entity has taken part as a competitor in one or more editions of the Olympic Games.
-
B.
hasOlympicCountry
Indicates that an entity is associated with or represents a specific country in the context of the Olympic Games.
-
C.
olympicParticipationType
Indicates the specific role or category of involvement an entity has in the Olympic Games (e.g., as an athlete, team, official, or other participation type).
-
D.
hasOlympians
Indicates that an entity includes, is associated with, or contains one or more Olympian participants or members.
-
E.
numberOfOlympicAppearances
Indicates the total count of times an entity has participated in 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_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64c04ac408190bab8dfadcc002deb |
completed | May 2, 2026, 7:09 p.m. |
| PD | Predicate disambiguation | batch_69f641e2f1708190b45b48d6a43c51d2 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 12:40 a.m.