Triple
T5826663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridge to Bridge rowing races |
E129241
|
entity |
| Predicate | relatedSport |
P67409
|
FINISHED |
| Object | canoe racing |
—
|
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: canoe racing | Statement: [Bridge to Bridge rowing races, relatedSport, canoe racing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedSport Context triple: [Bridge to Bridge rowing races, relatedSport, canoe racing]
-
A.
popularSport
Indicates that a sport is widely liked, followed, or played by many people within a certain group or region.
-
B.
tenantSport
Indicates that a tenant participates in or is associated with a particular sport.
-
C.
sportsInvolvement
Indicates the nature or extent of an entity’s participation in, association with, or role within a sport or sporting activity.
-
D.
basedInSport
Indicates that an entity (such as a team, organization, or person) is primarily associated with or operates within a particular sport.
-
E.
favoriteSport
Indicates that one entity has a particular sport that it prefers above all others.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c044a9c4f0819081b8c196932883f6 |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:53 p.m.