Triple
T13418197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lofotodden National Park |
E313268
|
entity |
| Predicate | locatedInMunicipality |
P40
|
FINISHED |
| Object | Moskenes |
E1039697
|
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: Moskenes | Statement: [Lofotodden National Park, locatedInMunicipality, Moskenes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moskenes Context triple: [Lofotodden National Park, locatedInMunicipality, Moskenes]
-
A.
Moskenes
chosen
Moskenes is a coastal municipality in Nordland county, Norway, known for its dramatic Lofoten archipelago landscapes, fishing villages, and tourism.
-
B.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
-
C.
Hvalsey
Hvalsey is the best-preserved Norse ruin site in Greenland, known for its stone church and remnants of a medieval farming settlement.
-
D.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
E.
Nesodden
Nesodden is a municipality and peninsula in southeastern Norway, situated across the Oslofjord from the capital city of Oslo.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb8416c8190a00dde0917c26f51 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76ba16b948190b7e753368eabf012 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:39 p.m.