Triple
T14307022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sør-Aurdal |
E354723
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Nesbyen |
E440168
|
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: Nesbyen | Statement: [Sør-Aurdal, borderedBy, Nesbyen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nesbyen Context triple: [Sør-Aurdal, borderedBy, Nesbyen]
-
A.
Nesbyen
chosen
Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
-
B.
Teigebyen
Teigebyen is a village in Viken county, Norway, serving as the main local hub for municipal services and community life in Nannestad.
-
C.
Enebakk
Enebakk is a rural municipality in Viken county, Norway, known for its forests, lakes, and proximity to the Oslo metropolitan area.
-
D.
Nesseby
Nesseby is a small coastal municipality in Troms og Finnmark county in northern Norway, known for its Sámi culture and location along the Varangerfjorden.
-
E.
Nadderud
Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b156b0819083f2bd319deed1b6 |
completed | April 14, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d2c32648190bc8bb26d57df57f5 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:12 a.m.