Triple
T22309955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bear Island |
E551485
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object |
Miseryfjellet
Miseryfjellet is the tallest mountain on Norway’s remote Bear Island in the Barents Sea, known for its rugged Arctic landscape and challenging weather conditions.
|
E1529842
|
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: Miseryfjellet | Statement: [Bear Island, highestPoint, Miseryfjellet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miseryfjellet Context triple: [Bear Island, highestPoint, Miseryfjellet]
-
A.
Heilefjellet
Heilefjellet is a mountain located in the coastal municipality of Bremanger in Vestland county, western Norway.
-
B.
Milorgfjella
Milorgfjella is a mountain subrange in Queen Maud Land, Antarctica, forming part of the larger Heimefront Range.
-
C.
Etnefjellet
Etnefjellet is a mountainous area in western Norway known for its rugged terrain, hiking opportunities, and scenic natural landscapes.
-
D.
Mount Mefjell
Mount Mefjell is a mountain located within the Sør Rondane range in Queen Maud Land, Antarctica.
-
E.
Ramnefjellet
Ramnefjellet is a mountain in Norway best known for the massive rockslides in the early 20th century that caused catastrophic tsunamis in the nearby lake Lovatnet.
- 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: Miseryfjellet Triple: [Bear Island, highestPoint, Miseryfjellet]
Generated description
Miseryfjellet is the tallest mountain on Norway’s remote Bear Island in the Barents Sea, known for its rugged Arctic landscape and challenging weather conditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Miseryfjellet Target entity description: Miseryfjellet is the tallest mountain on Norway’s remote Bear Island in the Barents Sea, known for its rugged Arctic landscape and challenging weather conditions.
-
A.
Heilefjellet
Heilefjellet is a mountain located in the coastal municipality of Bremanger in Vestland county, western Norway.
-
B.
Milorgfjella
Milorgfjella is a mountain subrange in Queen Maud Land, Antarctica, forming part of the larger Heimefront Range.
-
C.
Etnefjellet
Etnefjellet is a mountainous area in western Norway known for its rugged terrain, hiking opportunities, and scenic natural landscapes.
-
D.
Mount Mefjell
Mount Mefjell is a mountain located within the Sør Rondane range in Queen Maud Land, Antarctica.
-
E.
Ramnefjellet
Ramnefjellet is a mountain in Norway best known for the massive rockslides in the early 20th century that caused catastrophic tsunamis in the nearby lake Lovatnet.
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1574d53148190a1ec07f849e1ae9d |
completed | April 29, 2026, 12:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0acca39c4c8190a418ec2ff1434122 |
completed | May 18, 2026, 8:24 a.m. |
| NEDg | Description generation | batch_6a0acf8c37d48190990bc7e1152f98b3 |
completed | May 18, 2026, 8:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0acff349248190a13968f340cdebcf |
completed | May 18, 2026, 8:38 a.m. |
Created at: April 16, 2026, 8:42 p.m.