Triple
T19822265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svenska Spel |
E476223
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
Stryktipset
Stryktipset is a popular Swedish football betting game, best known for its weekly pools where players predict the outcomes of 13 matches.
|
E1397441
|
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: Stryktipset | Statement: [Svenska Spel, brand, Stryktipset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stryktipset Context triple: [Svenska Spel, brand, Stryktipset]
-
A.
Triobet
Triobet is an online sports betting and gaming company known for sponsoring various sporting events and leagues in the Baltic region.
-
B.
Totolapan
Totolapan is a small town in the Mexican state of Morelos known for its traditional rural character and role as the administrative center of its surrounding municipality.
-
C.
Totesport
Totesport is a British betting and gaming company known for its involvement in horse racing and sports wagering.
-
D.
Betfred
Betfred is a major UK-based bookmaker and online gambling company known for its extensive sports betting and gaming operations.
-
E.
Betclic
Betclic is a European online sports betting and gambling company known for sponsoring major professional sports leagues and events.
- 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: Stryktipset Triple: [Svenska Spel, brand, Stryktipset]
Generated description
Stryktipset is a popular Swedish football betting game, best known for its weekly pools where players predict the outcomes of 13 matches.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stryktipset Target entity description: Stryktipset is a popular Swedish football betting game, best known for its weekly pools where players predict the outcomes of 13 matches.
-
A.
Triobet
Triobet is an online sports betting and gaming company known for sponsoring various sporting events and leagues in the Baltic region.
-
B.
Totolapan
Totolapan is a small town in the Mexican state of Morelos known for its traditional rural character and role as the administrative center of its surrounding municipality.
-
C.
Totesport
Totesport is a British betting and gaming company known for its involvement in horse racing and sports wagering.
-
D.
Betfred
Betfred is a major UK-based bookmaker and online gambling company known for its extensive sports betting and gaming operations.
-
E.
Betclic
Betclic is a European online sports betting and gambling company known for sponsoring major professional sports leagues and events.
- F. None of above. chosen
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.