Triple
T4346216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betfred |
E97908
|
entity |
| Predicate | originalName |
P65
|
FINISHED |
| Object | Done Bookmakers |
E97908
|
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: Done Bookmakers | Statement: [Betfred, originalName, Done Bookmakers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Done Bookmakers Context triple: [Betfred, originalName, Done Bookmakers]
-
A.
Betfair
Betfair is a major online gambling company and betting exchange based in the United Kingdom.
-
B.
Bet365
Bet365 is a major British online gambling company best known for its sports betting platform and global sponsorships in horse racing and football.
-
C.
Betfred
chosen
Betfred is a major UK-based bookmaker and online gambling company known for its extensive sports betting and gaming operations.
-
D.
Afabet
Afabet is a town in Eritrea known historically as a key site during the Eritrean War of Independence.
-
E.
Bets
Bets is a young girl who serves as one of the child detectives in Enid Blyton’s “The Mystery Series,” contributing curiosity and insight to the group’s investigations.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3518d6728819084a2f40ae0bd3ac8 |
completed | March 12, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5dba958b88190b1b4efe4274cd060 |
completed | March 14, 2026, 10:05 p.m. |
Created at: March 12, 2026, 11:15 p.m.