Triple
T20018763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rissa (former municipality) |
E494791
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Stadsbygd
Stadsbygd is a village and former administrative center in Trøndelag county, Norway, known for its rural coastal setting and historical church.
|
E1407213
|
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: Stadsbygd | Statement: [Rissa (former municipality), contains, Stadsbygd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stadsbygd Context triple: [Rissa (former municipality), contains, Stadsbygd]
-
A.
Stangebyen
Stangebyen is a village in Innlandet county, Norway, serving as the main local hub for services, commerce, and administration in the Stange area.
-
B.
Stadlandet
Stadlandet is a rugged coastal peninsula in western Norway known for its exposed position to the North Atlantic and challenging maritime conditions.
-
C.
Bjørheimsbygd
Bjørheimsbygd is a small village in Strand municipality in Rogaland county, southwestern Norway.
-
D.
Smestad
Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
-
E.
Stålstaden
Stålstaden is a Swedish city nickname referring to Eskilstuna’s historic role as a major steel and metalworking industrial center.
- 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: Stadsbygd Triple: [Rissa (former municipality), contains, Stadsbygd]
Generated description
Stadsbygd is a village and former administrative center in Trøndelag county, Norway, known for its rural coastal setting and historical church.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stadsbygd Target entity description: Stadsbygd is a village and former administrative center in Trøndelag county, Norway, known for its rural coastal setting and historical church.
-
A.
Stangebyen
Stangebyen is a village in Innlandet county, Norway, serving as the main local hub for services, commerce, and administration in the Stange area.
-
B.
Stadlandet
Stadlandet is a rugged coastal peninsula in western Norway known for its exposed position to the North Atlantic and challenging maritime conditions.
-
C.
Bjørheimsbygd
Bjørheimsbygd is a small village in Strand municipality in Rogaland county, southwestern Norway.
-
D.
Smestad
Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
-
E.
Stålstaden
Stålstaden is a Swedish city nickname referring to Eskilstuna’s historic role as a major steel and metalworking industrial center.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623e40748190b1abb0ead9acab4e |
completed | April 20, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a080e286230819097e564d028e73ab5 |
completed | May 16, 2026, 6:26 a.m. |
| NEDg | Description generation | batch_6a080ef87f08819091b4a76009b1c4ba |
completed | May 16, 2026, 6:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a080f8bb81c819098d39ad6e1642aa8 |
completed | May 16, 2026, 6:32 a.m. |
Created at: April 11, 2026, 3:34 p.m.