Triple
T16262693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nesodden |
E394792
|
entity |
| Predicate | capitalOfMunicipality |
P15510
|
FINISHED |
| Object | Nesoddtangen |
E670527
|
NE FINISHED |
How this triple was built (2 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: Nesoddtangen | Statement: [Nesodden, capitalOfMunicipality, Nesoddtangen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nesoddtangen Context triple: [Nesodden, capitalOfMunicipality, Nesoddtangen]
-
A.
Nesoddtangen
chosen
Nesoddtangen is a village and administrative center in Nesodden municipality in Viken county, Norway, located on a peninsula directly across the Oslofjord from central Oslo.
-
B.
Rudshøgda
Rudshøgda is a small village in Ringsaker Municipality in Innlandet county, Norway, known for its location along major transport routes and its association with author Alf Prøysen.
-
C.
Rennesøyhodnet
Rennesøyhodnet is the prominent hill that forms the highest natural point on the island of Rennesøy in Rogaland county, Norway.
-
D.
Hisingen
Hisingen is a large island and district in Gothenburg, Sweden, known for its industrial areas, shipyards, and rapidly developing residential and tech hubs.
-
E.
Bispevika
Bispevika is a redeveloped waterfront district in Oslo, Norway, featuring modern residential, commercial, and cultural spaces along the city’s inner harbor.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c5583c8190901e892238cf8dbd |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0091855ab48190a14ad7df9cd806ad |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:04 a.m.