Triple
T22490828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hege Riise |
E556011
|
entity |
| Predicate | memberOfSportsTeam |
P330
|
FINISHED |
| Object |
SK Snøgg
SK Snøgg is a Norwegian sports club best known for its football team, which has featured prominent players such as Hege Riise.
|
E1538896
|
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: SK Snøgg | Statement: [Hege Riise, memberOfSportsTeam, SK Snøgg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SK Snøgg Context triple: [Hege Riise, memberOfSportsTeam, SK Snøgg]
-
A.
Sno
Sno is a small mountain village in northeastern Georgia’s Kazbegi region, known for its traditional stone towers and scenic Caucasus landscapes.
-
B.
Snovsk
Snovsk is a small town in northern Ukraine known historically as a regional railway and industrial center.
-
C.
Knudsker
Knudsker is a small settlement on the Danish island of Bornholm, known for its rural character and proximity to the town of Rønne.
-
D.
Skeid
Skeid is a Norwegian sports club best known for its football team and local rivalry with Lyn in Oslo.
-
E.
Skjelten
Skjelten is a small settlement in the municipality of Ørskog in Møre og Romsdal county, Norway.
- 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: SK Snøgg Triple: [Hege Riise, memberOfSportsTeam, SK Snøgg]
Generated description
SK Snøgg is a Norwegian sports club best known for its football team, which has featured prominent players such as Hege Riise.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SK Snøgg Target entity description: SK Snøgg is a Norwegian sports club best known for its football team, which has featured prominent players such as Hege Riise.
-
A.
Sno
Sno is a small mountain village in northeastern Georgia’s Kazbegi region, known for its traditional stone towers and scenic Caucasus landscapes.
-
B.
Snovsk
Snovsk is a small town in northern Ukraine known historically as a regional railway and industrial center.
-
C.
Knudsker
Knudsker is a small settlement on the Danish island of Bornholm, known for its rural character and proximity to the town of Rønne.
-
D.
Skeid
Skeid is a Norwegian sports club best known for its football team and local rivalry with Lyn in Oslo.
-
E.
Skjelten
Skjelten is a small settlement in the municipality of Ørskog in Møre og Romsdal county, Norway.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c40930c81908310ac6afd98c62e |
completed | April 29, 2026, 1:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b1269d2008190a2ecdfec3d1b4369 |
completed | May 18, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_6a0b14b8a3a48190bc3826bf72231df9 |
completed | May 18, 2026, 1:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b1514991c8190b1c26422aa7d68fd |
completed | May 18, 2026, 1:33 p.m. |
Created at: April 16, 2026, 8:49 p.m.