Triple
T13798962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skibladner |
E331588
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | White Swan of Mjøsa |
E65750
|
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: White Swan of Mjøsa | Statement: [Skibladner, nickname, White Swan of Mjøsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: White Swan of Mjøsa Context triple: [Skibladner, nickname, White Swan of Mjøsa]
-
A.
Sognsvann
Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
-
B.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
-
C.
Finnsnes
Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
-
D.
Sandnessjøen
Sandnessjøen is a coastal town in northern Norway known as a regional hub for the Helgeland area, with strong ties to maritime industries and access to the surrounding archipelago and mountains.
-
E.
Mjøsa Lake
chosen
Mjøsa Lake is Norway’s largest lake, located in the southeastern part of the country and known for its scenic surroundings and historic towns along its shores.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ce9148190b23370f6a522ff7a |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0893a20819081d4001b8dbc9c36 |
completed | May 3, 2026, 8:31 p.m. |
Created at: April 9, 2026, 10:11 p.m.