Triple
T15360403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sykkylven |
E367273
|
entity |
| Predicate | hasCompany |
P1287
|
FINISHED |
| Object |
Ekornes
Ekornes is a Norwegian furniture manufacturer best known for its Stressless line of reclining chairs and sofas.
|
E1154226
|
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: Ekornes | Statement: [Sykkylven, hasCompany, Ekornes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ekornes Context triple: [Sykkylven, hasCompany, Ekornes]
-
A.
Ornes
Ornes is a French village in the Meuse department that was completely destroyed during the Battle of Verdun in World War I and left as an uninhabited memorial site.
-
B.
Lofsrud
Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
-
C.
Rygge
Rygge is a municipality in southeastern Norway, historically known for its military air station and proximity to the town of Moss.
-
D.
Hestnes
Hestnes is a small settlement located within the municipality of Eigersund in Rogaland county, southwestern Norway.
-
E.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
- 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: Ekornes Triple: [Sykkylven, hasCompany, Ekornes]
Generated description
Ekornes is a Norwegian furniture manufacturer best known for its Stressless line of reclining chairs and sofas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ekornes Target entity description: Ekornes is a Norwegian furniture manufacturer best known for its Stressless line of reclining chairs and sofas.
-
A.
Ornes
Ornes is a French village in the Meuse department that was completely destroyed during the Battle of Verdun in World War I and left as an uninhabited memorial site.
-
B.
Lofsrud
Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
-
C.
Rygge
Rygge is a municipality in southeastern Norway, historically known for its military air station and proximity to the town of Moss.
-
D.
Hestnes
Hestnes is a small settlement located within the municipality of Eigersund in Rogaland county, southwestern Norway.
-
E.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4607408190ab281a7f7a8012d3 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1343862481908962dfe0ab946b97 |
completed | May 9, 2026, 10:58 a.m. |
| NEDg | Description generation | batch_69ff143c0e448190b4775711ee7545d1 |
completed | May 9, 2026, 11:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff14e1a7b881909ad2ba0d35847ea1 |
completed | May 9, 2026, 11:05 a.m. |
Created at: April 10, 2026, 3:18 a.m.