Triple
T11788457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rovaniemi |
E280329
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
Arktikum
Arktikum is a museum and science center in Rovaniemi, Finland, focusing on Arctic nature, culture, and research.
|
E276631
|
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: Arktikum | Statement: [Rovaniemi, hasAttraction, Arktikum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arktikum Context triple: [Rovaniemi, hasAttraction, Arktikum]
-
A.
Arktikugol
Arktikugol is a Russian state-owned coal mining company best known for operating mining settlements in the Svalbard archipelago.
-
B.
Campo de Hielo Norte
Campo de Hielo Norte is a vast Patagonian ice field in southern Chile, known as one of the largest mid-latitude ice masses in the world and a major source of outlet glaciers and freshwater.
-
C.
Barentu
Barentu is a town in western Eritrea that serves as an important regional center in the Gash-Barka administrative region.
-
D.
Naukan
Naukan is a former indigenous Yupik settlement located at the easternmost point of the Chukotka Peninsula in Russia, near the Bering Strait.
-
E.
Polaria
Polaria is an Arctic-themed experience center and aquarium in Tromsø, Norway, focusing on polar research, climate, and marine life.
- 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: Arktikum Triple: [Rovaniemi, hasAttraction, Arktikum]
Generated description
Arktikum is a museum and science center in Rovaniemi, Finland, focusing on Arctic nature, culture, and research.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arktikum Target entity description: Arktikum is a museum and science center in Rovaniemi, Finland, focusing on Arctic nature, culture, and research.
-
A.
Arktikugol
Arktikugol is a Russian state-owned coal mining company best known for operating mining settlements in the Svalbard archipelago.
-
B.
Campo de Hielo Norte
Campo de Hielo Norte is a vast Patagonian ice field in southern Chile, known as one of the largest mid-latitude ice masses in the world and a major source of outlet glaciers and freshwater.
-
C.
Barentu
Barentu is a town in western Eritrea that serves as an important regional center in the Gash-Barka administrative region.
-
D.
Naukan
Naukan is a former indigenous Yupik settlement located at the easternmost point of the Chukotka Peninsula in Russia, near the Bering Strait.
-
E.
Polaria
chosen
Polaria is an Arctic-themed experience center and aquarium in Tromsø, Norway, focusing on polar research, climate, and marine life.
- F. None of above.
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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a587c2d881909297c3a6c7d26080 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f090f62bdc8190a8fd145839aef554 |
completed | April 28, 2026, 10:50 a.m. |
| NEDg | Description generation | batch_69f0bd3f39608190b29027b30664bd9c |
completed | April 28, 2026, 1:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f0ef5afd448190953b5d9929478132 |
completed | April 28, 2026, 5:33 p.m. |
Created at: April 8, 2026, 9:42 p.m.