Triple
T10688975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kilchberg |
E251955
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Naustdal
Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
|
E908103
|
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: Naustdal | Statement: [Kilchberg, hasTwinTown, Naustdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naustdal Context triple: [Kilchberg, hasTwinTown, Naustdal]
-
A.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
B.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
-
C.
Valldal
Valldal is a village in western Norway known for its scenic fjord landscape and strawberry farming, situated in the county of Møre og Romsdal.
-
D.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
E.
Årdal
Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
- 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: Naustdal Triple: [Kilchberg, hasTwinTown, Naustdal]
Generated description
Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Naustdal Target entity description: Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
-
A.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
B.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
-
C.
Valldal
Valldal is a village in western Norway known for its scenic fjord landscape and strawberry farming, situated in the county of Møre og Romsdal.
-
D.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
E.
Årdal
Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd1aef888190ba92474af3a49e36 |
completed | April 9, 2026, 1:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e46262a8f88190869c2161c3b10a19 |
completed | April 19, 2026, 5:04 a.m. |
| NEDg | Description generation | batch_69e4666f98ac81908b3d3b8a6a8af8c9 |
completed | April 19, 2026, 5:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e46c3f28dc8190a521c00151b01fde |
completed | April 19, 2026, 5:46 a.m. |
Created at: April 8, 2026, 9:11 p.m.