Triple
T21047792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordic skiing events at the 1952 Winter Olympics |
E518493
|
entity |
| Predicate | venue |
P373
|
FINISHED |
| Object | Norefjell |
—
|
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: Norefjell | Statement: [Nordic skiing events at the 1952 Winter Olympics, venue, Norefjell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norefjell Context triple: [Nordic skiing events at the 1952 Winter Olympics, venue, Norefjell]
-
A.
Norefjell
chosen
Norefjell is a prominent Norwegian mountain range and ski resort area known for its alpine terrain and winter sports facilities.
-
B.
Slettefjell
Slettefjell is a mountain in Norway known for its scenic highland landscapes and popular hiking and skiing routes.
-
C.
Høgefjellet
Høgefjellet is a mountain located on the island of Vågsøy in Vestland county, western Norway.
-
D.
Fonnfjellet
Fonnfjellet is a mountain located in the municipality of Meråker in Trøndelag county, central Norway.
-
E.
Narvikfjellet
Narvikfjellet is a Norwegian mountain and ski resort near Narvik, known for its scenic fjord views and opportunities for skiing and outdoor recreation.
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcf5b01481909db49aa5be3846aa |
completed | April 21, 2026, 4:28 a.m. |
Created at: April 16, 2026, 2:34 p.m.