Triple
T2945483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lofoten |
E79490
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object |
Gimsøya
Gimsøya is an island in Norway’s Lofoten archipelago, known for its dramatic coastal scenery, mountains, and Arctic landscapes.
|
E323763
|
NE FINISHED |
How this triple was built (4 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: Gimsøya | Statement: [Lofoten, hasIsland, Gimsøya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gimsøya Context triple: [Lofoten, hasIsland, Gimsøya]
-
A.
Vadsøya
Vadsøya is a small island in northern Norway that forms part of the town of Vadsø, known for its Arctic coastal setting and historical significance in Finnmark.
-
B.
Moskenesøya
Moskenesøya is a rugged island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and scenic coastal landscapes.
-
C.
Flakstadøya
Flakstadøya is a scenic island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and coastal landscapes.
-
D.
Bleikøya
Bleikøya is a small island in the inner Oslofjord near Oslo, Norway, known for its recreational areas and scenic coastal landscape.
-
E.
Barøya
Barøya is an island located in northern Norway within the Ofotfjord, known for its rugged coastal landscape and Arctic maritime environment.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gimsøya Triple: [Lofoten, hasIsland, Gimsøya]
Generated description
Gimsøya is an island in Norway’s Lofoten archipelago, known for its dramatic coastal scenery, mountains, and Arctic landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gimsøya Target entity description: Gimsøya is an island in Norway’s Lofoten archipelago, known for its dramatic coastal scenery, mountains, and Arctic landscapes.
-
A.
Vadsøya
Vadsøya is a small island in northern Norway that forms part of the town of Vadsø, known for its Arctic coastal setting and historical significance in Finnmark.
-
B.
Moskenesøya
Moskenesøya is a rugged island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and scenic coastal landscapes.
-
C.
Flakstadøya
Flakstadøya is a scenic island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and coastal landscapes.
-
D.
Bleikøya
Bleikøya is a small island in the inner Oslofjord near Oslo, Norway, known for its recreational areas and scenic coastal landscape.
-
E.
Barøya
Barøya is an island located in northern Norway within the Ofotfjord, known for its rugged coastal landscape and Arctic maritime environment.
- F. None of above. chosen
Provenance (5 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98b2752481908ec6f9a9cc24c0a7 |
completed | March 8, 2026, 3:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1eedb51b88190b7a009d45361fd32 |
completed | March 11, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69b1f2fd518881908fe555d2869b1d59 |
completed | March 11, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1f35c16548190b3ec9764cf812497 |
completed | March 11, 2026, 10:57 p.m. |
Created at: March 8, 2026, 2:56 p.m.