Triple
T15360348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sula |
E367272
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Giske |
E370242
|
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: Giske | Statement: [Sula, neighboringMunicipality, Giske]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Giske Context triple: [Sula, neighboringMunicipality, Giske]
-
A.
Giske
chosen
Giske is a coastal municipality in Møre og Romsdal county, Norway, known for its islands, fishing communities, and proximity to the town of Ålesund.
-
B.
Bjorli
Bjorli is a Norwegian village known for its ski resort and scenic mountain surroundings in Innlandet county.
-
C.
Bjerke
Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
-
D.
Gröndal
Gröndal is a residential district in southern Stockholm, Sweden, known for its waterfront location on Lake Mälaren and mix of early 20th-century and modern architecture.
-
E.
Suldal
Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4607408190ab281a7f7a8012d3 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56b4c6c881908ac7887a88f80829 |
completed | May 9, 2026, 3:45 p.m. |
Created at: April 10, 2026, 3:18 a.m.