Triple
T4587941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innherred |
E103413
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Snåsa
Snåsa is a rural municipality in Trøndelag county, Norway, known for its large lakes, forests, and strong South Sámi cultural heritage.
|
E486509
|
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: Snåsa | Statement: [Innherred, contains, Snåsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snåsa Context triple: [Innherred, contains, Snåsa]
-
A.
Finnsnes
Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
-
B.
Solbo
Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
-
C.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
D.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
E.
Ullensvang
Ullensvang is a scenic municipality in Vestland county, Norway, known for its fruit orchards, fjord landscapes, and location along the Hardangerfjord.
- 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: Snåsa Triple: [Innherred, contains, Snåsa]
Generated description
Snåsa is a rural municipality in Trøndelag county, Norway, known for its large lakes, forests, and strong South Sámi cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Snåsa Target entity description: Snåsa is a rural municipality in Trøndelag county, Norway, known for its large lakes, forests, and strong South Sámi cultural heritage.
-
A.
Finnsnes
Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
-
B.
Solbo
Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
-
C.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
D.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
E.
Ullensvang
Ullensvang is a scenic municipality in Vestland county, Norway, known for its fruit orchards, fjord landscapes, and location along the Hardangerfjord.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd591fc20481908d8d4b71d055ae8c |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be922507408190bf3923699da57d95 |
completed | March 21, 2026, 12:42 p.m. |
| NEDg | Description generation | batch_69be941b4df481909324cbb119b4e5ed |
completed | March 21, 2026, 12:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be947706f88190a25c72696290d92e |
completed | March 21, 2026, 12:52 p.m. |
Created at: March 20, 2026, 1:11 p.m.