Triple
T20114269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strømsø |
E490412
|
entity |
| Predicate | hasNearbyDistrict |
P4647
|
FINISHED |
| Object |
Åssiden
Åssiden is a residential district in Drammen, Norway, known for its riverside location along the Drammenselva and access to outdoor recreation areas.
|
E1411258
|
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: Åssiden | Statement: [Strømsø, hasNearbyDistrict, Åssiden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Åssiden Context triple: [Strømsø, hasNearbyDistrict, Åssiden]
-
A.
Åsnes
Åsnes is a rural municipality in Innlandet county in eastern Norway, known for its forests, agriculture, and location in the traditional region of Solør.
-
B.
Åsskard
Åsskard was a former municipality in Møre og Romsdal county, Norway, that was incorporated into the larger municipality of Surnadal.
-
C.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Nadderud
Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
- 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: Åssiden Triple: [Strømsø, hasNearbyDistrict, Åssiden]
Generated description
Åssiden is a residential district in Drammen, Norway, known for its riverside location along the Drammenselva and access to outdoor recreation areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Åssiden Target entity description: Åssiden is a residential district in Drammen, Norway, known for its riverside location along the Drammenselva and access to outdoor recreation areas.
-
A.
Åsnes
Åsnes is a rural municipality in Innlandet county in eastern Norway, known for its forests, agriculture, and location in the traditional region of Solør.
-
B.
Åsskard
Åsskard was a former municipality in Møre og Romsdal county, Norway, that was incorporated into the larger municipality of Surnadal.
-
C.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Nadderud
Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666e31af081908d8e0c867c388a73 |
completed | April 20, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08271c02b481908131cf1afc7ab027 |
completed | May 16, 2026, 8:13 a.m. |
| NEDg | Description generation | batch_6a082800b084819089a32a683d59f9d9 |
completed | May 16, 2026, 8:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0828572b088190abcbbdfb568b3c9d |
completed | May 16, 2026, 8:18 a.m. |
Created at: April 11, 2026, 11:29 p.m.