Triple
T17727172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vangsmjøse |
E442491
|
entity |
| Predicate | hasAlternativeSpelling |
P457
|
FINISHED |
| Object | Vangsmjøsa |
—
|
NE NERFINISHED |
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: Vangsmjøsa | Statement: [Vangsmjøse, hasAlternativeSpelling, Vangsmjøsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vangsmjøsa Context triple: [Vangsmjøse, hasAlternativeSpelling, Vangsmjøsa]
-
A.
Vangsmjøse
chosen
Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
-
B.
Vossevangen
Vossevangen is a village in western Norway that serves as the main commercial and cultural hub of the Voss region, known for its scenic surroundings and outdoor activities.
-
C.
Sjusjøen
Sjusjøen is a popular Norwegian cross-country skiing destination and mountain village known for its extensive trail network and scenic highland landscapes near Lillehammer.
-
D.
Verdalsøra
Verdalsøra is a small town in Trøndelag county, Norway, known for its riverside setting and role as a local commercial and service hub.
-
E.
Maridalsvannet
Maridalsvannet is the largest lake supplying drinking water to Oslo, Norway, and a popular nearby recreation area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e3cb708190b47456ad2008a65e |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 10:07 a.m.