Triple
T18915011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tolga |
E462702
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Hodalen
Hodalen is a small rural village in Tolga Municipality in Innlandet county, Norway, known for its scenic mountain and lake landscapes.
|
E1445607
|
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: Hodalen | Statement: [Tolga, hasSettlement, Hodalen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hodalen Context triple: [Tolga, hasSettlement, Hodalen]
-
A.
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.
-
B.
Lysthaugen
Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
-
C.
Heidal
Heidal is a village in Innlandet county, Norway, known for its traditional wooden architecture and scenic location in the Gudbrandsdalen valley.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial areas.
- 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: Hodalen Triple: [Tolga, hasSettlement, Hodalen]
Generated description
Hodalen is a small rural village in Tolga Municipality in Innlandet county, Norway, known for its scenic mountain and lake landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hodalen Target entity description: Hodalen is a small rural village in Tolga Municipality in Innlandet county, Norway, known for its scenic mountain and lake landscapes.
-
A.
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.
-
B.
Lysthaugen
Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
-
C.
Heidal
Heidal is a village in Innlandet county, Norway, known for its traditional wooden architecture and scenic location in the Gudbrandsdalen valley.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial areas.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c62685408190b17280147e1c247a |
completed | April 20, 2026, 6:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08d7c569a481909b595b0517fbee7d |
completed | May 16, 2026, 8:47 p.m. |
| NEDg | Description generation | batch_6a08d902cab481908d0a7b28699a2031 |
completed | May 16, 2026, 8:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08d9693acc8190acc75cbbf06b62da |
completed | May 16, 2026, 8:54 p.m. |
Created at: April 10, 2026, 11:58 a.m.