Triple
T4434739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European route E134 |
E95620
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Notodden |
E116895
|
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: Notodden | Statement: [European route E134, passesNear, Notodden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Notodden Context triple: [European route E134, passesNear, Notodden]
-
A.
Notodden
chosen
Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
-
B.
Ofoten
Ofoten is a district in Nordland county in northern Norway, known for its fjords, mountains, and the port town of Narvik.
-
C.
Sandvika
Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
-
D.
Raufoss
Raufoss is an industrial town in Norway known for its manufacturing sector, particularly in defense and automotive components.
-
E.
Røros
Røros is a historic Norwegian mining town and UNESCO World Heritage Site known for its well-preserved wooden buildings and copper mining heritage.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35588e99881908fea7b71a33e2bb6 |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67ac56548190a2d52b055cb48e8e |
completed | March 21, 2026, 9:41 a.m. |
Created at: March 12, 2026, 11:31 p.m.