Triple
T13781893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matchroom Sport |
E331150
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Barry Hearn |
E619588
|
NE 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: Barry Hearn | Statement: [Matchroom Sport, foundedBy, Barry Hearn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barry Hearn Context triple: [Matchroom Sport, foundedBy, Barry Hearn]
-
A.
Barry Hearn
chosen
Barry Hearn is a British sports promoter and businessman best known for transforming snooker, darts, and boxing into major televised events through his company Matchroom Sport.
-
B.
Jimmy Hill
Jimmy Hill was an influential English footballer, manager, and broadcaster who became a household name in the UK for his pioneering role in football and his long-running television punditry.
-
C.
Alan Dye
Alan Dye is a prominent industrial designer best known for leading user interface design at Apple, where he has played a key role in shaping the look and feel of the company’s software platforms.
-
D.
Charles Ainley
Charles Ainley is an individual notable enough to be recognized as a prominent bearer of the surname Ainley.
-
E.
Barry Spikings
Barry Spikings is a British film producer best known for his work on acclaimed films of the 1970s and 1980s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0247ccc881908dad7b547221f15d |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b079013881908e9f5412e5dfb0b2 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:11 p.m.