Triple
T22749232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melhus |
E562643
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Skaun
Skaun is a rural municipality in Trøndelag county, Norway, known for its scenic landscapes, agriculture, and proximity to the city of Trondheim.
|
E1552883
|
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: Skaun | Statement: [Melhus, borderedBy, Skaun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skaun Context triple: [Melhus, borderedBy, Skaun]
-
A.
Skaugum
Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
-
B.
Skjåk
Skjåk is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, national parks, and dry inland climate.
-
C.
Skjelten
Skjelten is a small settlement in the municipality of Ørskog in Møre og Romsdal county, Norway.
-
D.
Skåbu
Skåbu is a mountain village in Innlandet county, Norway, known as one of the highest permanently inhabited settlements in the country.
-
E.
Snåsa
Snåsa is a rural municipality in Trøndelag county, Norway, known for its large lakes, forests, and strong South Sámi cultural heritage.
- 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: Skaun Triple: [Melhus, borderedBy, Skaun]
Generated description
Skaun is a rural municipality in Trøndelag county, Norway, known for its scenic landscapes, agriculture, and proximity to the city of Trondheim.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skaun Target entity description: Skaun is a rural municipality in Trøndelag county, Norway, known for its scenic landscapes, agriculture, and proximity to the city of Trondheim.
-
A.
Skaugum
Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
-
B.
Skjåk
Skjåk is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, national parks, and dry inland climate.
-
C.
Skjelten
Skjelten is a small settlement in the municipality of Ørskog in Møre og Romsdal county, Norway.
-
D.
Skåbu
Skåbu is a mountain village in Innlandet county, Norway, known as one of the highest permanently inhabited settlements in the country.
-
E.
Snåsa
Snåsa is a rural municipality in Trøndelag county, Norway, known for its large lakes, forests, and strong South Sámi cultural heritage.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b822988190b5368ac1f4e1d70a |
completed | April 29, 2026, 3:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b9810e474819087fd95b0c92fd431 |
completed | May 18, 2026, 10:52 p.m. |
| NEDg | Description generation | batch_6a0b98e33b78819084ac449dd47cc778 |
completed | May 18, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9996e05c8190ad2cb5704bb4c245 |
completed | May 18, 2026, 10:58 p.m. |
Created at: April 17, 2026, 3:24 p.m.