Triple
T3209338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilorin |
E67240
|
entity |
| Predicate | sportsPopular |
P251
|
FINISHED |
| Object | football |
—
|
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 | Statement: [Ilorin, sportsPopular, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsPopular Context triple: [Ilorin, sportsPopular, football]
-
A.
popularSport
chosen
Indicates that a sport is widely liked, followed, or played by many people within a certain group or region.
-
B.
sport
Indicates that an entity participates in, is associated with, or is characterized by a particular athletic activity or game.
-
C.
sportFocus
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
D.
sportsAndRecreation
Indicates a relationship where an entity is associated with, involved in, or designated for sports or recreational activities.
-
E.
sportsCount
Indicates the number of sports associated with or involved in a given entity or context.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaab701c48190b91404ab416f7ce3 |
completed | March 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69ad9e078f7c8190813d9fcb4f5071fb |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.