Triple
T19822268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svenska Spel |
E476223
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
Oddset
Oddset is a Swedish sports betting product offered by the state-owned gambling company Svenska Spel.
|
E476223
|
NE FINISHED |
How this triple was built (4 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: Oddset | Statement: [Svenska Spel, brand, Oddset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oddset Context triple: [Svenska Spel, brand, Oddset]
-
A.
Totesport
Totesport is a British betting and gaming company known for its involvement in horse racing and sports wagering.
-
B.
Svenska Spel
Svenska Spel is Sweden’s state-owned gambling company, operating national lotteries, sports betting, and casino games under government regulation.
-
C.
Paddy Power
Paddy Power is an Irish bookmaker and online gambling company known for its sports betting services and provocative marketing campaigns.
-
D.
Oslo Havn KF
Oslo Havn KF is the municipal enterprise responsible for managing and developing the Port of Oslo’s harbor infrastructure and maritime operations.
-
E.
Jyske Bank
Jyske Bank is one of Denmark’s largest financial institutions, offering a wide range of banking and financial services to individuals and businesses.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Oddset Triple: [Svenska Spel, brand, Oddset]
Generated description
Oddset is a Swedish sports betting product offered by the state-owned gambling company Svenska Spel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oddset Target entity description: Oddset is a Swedish sports betting product offered by the state-owned gambling company Svenska Spel.
-
A.
Totesport
Totesport is a British betting and gaming company known for its involvement in horse racing and sports wagering.
-
B.
Svenska Spel
chosen
Svenska Spel is Sweden’s state-owned gambling company, operating national lotteries, sports betting, and casino games under government regulation.
-
C.
Paddy Power
Paddy Power is an Irish bookmaker and online gambling company known for its sports betting services and provocative marketing campaigns.
-
D.
Oslo Havn KF
Oslo Havn KF is the municipal enterprise responsible for managing and developing the Port of Oslo’s harbor infrastructure and maritime operations.
-
E.
Jyske Bank
Jyske Bank is one of Denmark’s largest financial institutions, offering a wide range of banking and financial services to individuals and businesses.
- F. None of above.
Provenance (5 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654ffb37c8190be540a793befe16c |
completed | April 20, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ccd22b448190b447c893ee9ffd83 |
completed | May 16, 2026, 1:48 a.m. |
| NEDg | Description generation | batch_6a07cfe19c288190b360d1767e8fffa3 |
completed | May 16, 2026, 2:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d0c1cbc08190bffbc27457117b82 |
completed | May 16, 2026, 2:04 a.m. |
Created at: April 10, 2026, 1:50 p.m.