Triple
T8073505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region Nordjylland |
E188433
|
entity |
| Predicate | containsIsland |
P970
|
FINISHED |
| Object | Læsø |
E187329
|
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: Læsø | Statement: [Region Nordjylland, containsIsland, Læsø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Læsø Context triple: [Region Nordjylland, containsIsland, Læsø]
-
A.
Læsø
chosen
Læsø is a Danish island in the Kattegat known for its salt production, distinctive seaweed-roofed houses, and tranquil coastal landscapes.
-
B.
Hvidøen
Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
-
C.
Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
-
D.
Langeland
Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
-
E.
Lindøya
Lindøya is a small, scenic island in the Oslofjord known for its colorful wooden cottages, car-free environment, and popularity as a summer retreat near 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb404a98408190b6c8eecb95ad086d |
completed | March 31, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63ecb04881909b1849dc4ef7c2bc |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:27 p.m.