Triple
T13418129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European route E10 |
E313266
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Narvik |
E33599
|
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: Narvik | Statement: [European route E10, connects, Narvik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narvik Context triple: [European route E10, connects, Narvik]
-
A.
Narvik
chosen
Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
-
B.
Kiruna
Kiruna is a mining town in northern Sweden known for its large iron ore mine and its location above the Arctic Circle.
-
C.
Karasjok
Karasjok is a municipality in northern Norway known as a cultural and political center for the Sámi people.
-
D.
Notodden
Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
-
E.
Piteå
Piteå is a coastal town in northern Sweden known for its historic wooden architecture, archipelago, and role as a regional cultural and industrial center in Norrbotten County.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb8416c8190a00dde0917c26f51 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75475d7648190b050e44a5312d13d |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:39 p.m.