Triple
T11615787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haldenvassdraget |
E275502
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Skulerudsjøen
Skulerudsjøen is a lake in southeastern Norway that forms part of the Haldenvassdraget watercourse system.
|
E941414
|
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: Skulerudsjøen | Statement: [Haldenvassdraget, hasPart, Skulerudsjøen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skulerudsjøen Context triple: [Haldenvassdraget, hasPart, Skulerudsjøen]
-
A.
Sandnessjøen
Sandnessjøen is a coastal town in northern Norway known as a regional hub for the Helgeland area, with strong ties to maritime industries and access to the surrounding archipelago and mountains.
-
B.
Ensjø
Ensjø is a residential and former industrial neighborhood in Oslo, Norway, known for its ongoing urban redevelopment and good public transport connections.
-
C.
Strømsø
Strømsø is a historic district and former separate town that now forms part of the city of Drammen in Norway.
-
D.
Strynø
Strynø is a small Danish island in the Baltic Sea known for its rural charm, traditional village environment, and location between the larger islands of Langeland and Ærø.
-
E.
Rødenessjøen
Rødenessjøen is a lake in Norway known for its scenic natural surroundings and recreational opportunities such as fishing and boating.
- 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: Skulerudsjøen Triple: [Haldenvassdraget, hasPart, Skulerudsjøen]
Generated description
Skulerudsjøen is a lake in southeastern Norway that forms part of the Haldenvassdraget watercourse system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skulerudsjøen Target entity description: Skulerudsjøen is a lake in southeastern Norway that forms part of the Haldenvassdraget watercourse system.
-
A.
Sandnessjøen
Sandnessjøen is a coastal town in northern Norway known as a regional hub for the Helgeland area, with strong ties to maritime industries and access to the surrounding archipelago and mountains.
-
B.
Ensjø
Ensjø is a residential and former industrial neighborhood in Oslo, Norway, known for its ongoing urban redevelopment and good public transport connections.
-
C.
Strømsø
Strømsø is a historic district and former separate town that now forms part of the city of Drammen in Norway.
-
D.
Strynø
Strynø is a small Danish island in the Baltic Sea known for its rural charm, traditional village environment, and location between the larger islands of Langeland and Ærø.
-
E.
Rødenessjøen
Rødenessjøen is a lake in Norway known for its scenic natural surroundings and recreational opportunities such as fishing and boating.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a04675e08190837a3717242fd0f9 |
completed | April 10, 2026, 7:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef8287f2dc819089b14707e035f7a1 |
completed | April 27, 2026, 3:36 p.m. |
| NEDg | Description generation | batch_69ef96ab29d48190b225504856007384 |
completed | April 27, 2026, 5:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69efd64bfa7081909715aa64d80fadf3 |
completed | April 27, 2026, 9:34 p.m. |
Created at: April 8, 2026, 9:38 p.m.