Triple
T16242845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Askøy |
E394295
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object |
Hanøya
Hanøya is a small Norwegian island that is part of the Askøy municipality in Vestland county.
|
E1201975
|
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: Hanøya | Statement: [Askøy, hasIsland, Hanøya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanøya Context triple: [Askøy, hasIsland, Hanøya]
-
A.
Hankø
Hankø is a small Norwegian island and resort area known for its sailing, summer tourism, and scenic coastal landscapes.
-
B.
Helsingør
Helsingør is a historic coastal city in eastern Denmark, best known internationally as the setting of Shakespeare’s Hamlet (as Elsinore) and for its prominent Kronborg Castle overlooking the Øresund Strait.
-
C.
Copenhagen
Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
-
D.
Copenhagen
Copenhagen is a popular American smokeless tobacco (chewing tobacco/dip) brand known for its long history and strong presence in the U.S. market.
-
E.
Herning
Herning is a Danish city in the Central Jutland region known for its trade fairs, conference facilities, and vibrant cultural and sports events.
- 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: Hanøya Triple: [Askøy, hasIsland, Hanøya]
Generated description
Hanøya is a small Norwegian island that is part of the Askøy municipality in Vestland county.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hanøya Target entity description: Hanøya is a small Norwegian island that is part of the Askøy municipality in Vestland county.
-
A.
Hankø
Hankø is a small Norwegian island and resort area known for its sailing, summer tourism, and scenic coastal landscapes.
-
B.
Helsingør
Helsingør is a historic coastal city in eastern Denmark, best known internationally as the setting of Shakespeare’s Hamlet (as Elsinore) and for its prominent Kronborg Castle overlooking the Øresund Strait.
-
C.
Copenhagen
Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
-
D.
Copenhagen
Copenhagen is a popular American smokeless tobacco (chewing tobacco/dip) brand known for its long history and strong presence in the U.S. market.
-
E.
Herning
Herning is a Danish city in the Central Jutland region known for its trade fairs, conference facilities, and vibrant cultural and sports events.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24560060c8190ace4f4c0bd0d886d |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000edf64a88190a9dd0c591c742977 |
completed | May 10, 2026, 4:51 a.m. |
| NEDg | Description generation | batch_6a00108174ac8190b3c421b115b7190e |
completed | May 10, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0010f40d6081909927e8281ab17580 |
completed | May 10, 2026, 5 a.m. |
Created at: April 10, 2026, 5:04 a.m.