Triple
T14377213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guta lag |
E356505
|
entity |
| Predicate | appliesToTerritory |
P647
|
FINISHED |
| Object | Gotland |
E22241
|
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: Gotland | Statement: [Guta lag, appliesToTerritory, Gotland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gotland Context triple: [Guta lag, appliesToTerritory, Gotland]
-
A.
Gotland
chosen
Gotland is Sweden’s largest island, located in the Baltic Sea and known for its medieval town of Visby, limestone cliffs, and rich Viking-era history.
-
B.
Sylt
Sylt is a popular German North Sea island known for its long sandy beaches, distinctive dune landscapes, and status as an upscale holiday destination.
-
C.
Ölandet
Ölandet is one of the islands in the Pellinge archipelago off the southern coast of Finland, known for its coastal nature and traditional island scenery.
-
D.
Öland
Öland is Sweden’s second-largest island, known for its unique limestone plains, rich birdlife, and popular summer tourism along the Baltic Sea coast.
-
E.
Suðurland
Suðurland is a region in southern Iceland known for its dramatic landscapes, including waterfalls, glaciers, black sand beaches, and active volcanoes.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de900949fc81909be0da1734c46645 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5be63848190aa71f009ceaea1b3 |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 10, 2026, 1:16 a.m.