Triple
T15345233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulvik |
E366898
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object | Finse |
E508955
|
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: Finse | Statement: [Ulvik, hasAttraction, Finse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Finse Context triple: [Ulvik, hasAttraction, Finse]
-
A.
Finse
chosen
Finse is a remote mountain village and railway station in Norway, known as the highest point on the Bergen Line and a popular base for hiking and glacier activities.
-
B.
Loen
Loen is a small settlement located on Namu Atoll in the Marshall Islands, a remote Pacific island nation.
-
C.
Trysil
Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
-
D.
Sälen
Sälen is a Swedish mountain village and popular ski resort area in Dalarna, best known as the traditional starting point of the annual Vasaloppet cross-country ski race.
-
E.
Lognes
Lognes is a suburban commune in the eastern outskirts of Paris, France, known for its lakeside setting and role within the planned new town of Marne-la-Vallée.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e163a3c8190ab933411372c1573 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01f931408190828d87567cecaceb |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.