Triple
T10961329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ladbrokes |
E258979
|
entity |
| Predicate | focusSportForSponsorship |
P6214
|
FINISHED |
| Object | horse 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: horse racing | Statement: [Ladbrokes, focusSportForSponsorship, horse racing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusSportForSponsorship Context triple: [Ladbrokes, focusSportForSponsorship, horse racing]
-
A.
sponsorSport
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
-
B.
sportFocus
chosen
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
C.
sportsSponsored
Indicates that one entity provides financial or material sponsorship to support another entity’s sports-related activities or events.
-
D.
favoriteSport
Indicates that one entity has a particular sport that it prefers above all others.
-
E.
sportsBrand
Indicates that one entity is a sports-related brand or label associated with the other entity.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7712bf65c8190b847784d885876fd |
completed | April 9, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_69d72e874f48819096ffa878f90c7d5b |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.