Triple
T7346015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tøyen Torg |
E169380
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Tøyen torg (Norwegian) |
E169380
|
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: Tøyen torg (Norwegian) | Statement: [Tøyen Torg, hasAlternativeName, Tøyen torg (Norwegian)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tøyen torg (Norwegian) Context triple: [Tøyen Torg, hasAlternativeName, Tøyen torg (Norwegian)]
-
A.
Tøyen Torg
chosen
Tøyen Torg is a central square and commercial hub in Oslo’s Tøyen neighborhood, known for its shops, cafés, and multicultural urban atmosphere.
-
B.
Torvet (Trondheim main square)
Torvet is the central main square of Trondheim, Norway, serving as a historic and commercial hub for public gatherings, markets, and city events.
-
C.
Ringen via Tøyen
Ringen via Tøyen is a circular service pattern on the Oslo Metro that routes trains through Tøyen station before completing a loop.
-
D.
Tøyen
Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
-
E.
Trondheim Torg shopping center
Trondheim Torg shopping center is a central retail complex in downtown Trondheim, Norway, featuring a wide range of shops, dining options, and services.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0f0329c8190a0182e3bf62604e5 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa8de0888190b62101471048b8e1 |
completed | March 28, 2026, 3:58 p.m. |
Created at: March 27, 2026, 3:05 p.m.