Triple
T15332054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stad |
E366558
|
entity |
| Predicate | hasCoastlineOn |
P212
|
FINISHED |
| Object |
Sildegapet
Sildegapet is a coastal sea area adjacent to the municipality of Stad in western Norway, known for its rough waters and significance to local maritime routes.
|
E1149866
|
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: Sildegapet | Statement: [Stad, hasCoastlineOn, Sildegapet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sildegapet Context triple: [Stad, hasCoastlineOn, Sildegapet]
-
A.
Rapadalen
Rapadalen is a renowned, remote river valley in northern Sweden known for its dramatic alpine scenery and rich wildlife within Sarek National Park.
-
B.
Harpefoss
Harpefoss is a small village in Sør-Fron Municipality in Innlandet county, Norway, known for its scenic valley setting along the Gudbrandsdalslågen river.
-
C.
Tallkrogen
Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
-
D.
Follebu
Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
-
E.
Lysthaugen
Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
- 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: Sildegapet Triple: [Stad, hasCoastlineOn, Sildegapet]
Generated description
Sildegapet is a coastal sea area adjacent to the municipality of Stad in western Norway, known for its rough waters and significance to local maritime routes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sildegapet Target entity description: Sildegapet is a coastal sea area adjacent to the municipality of Stad in western Norway, known for its rough waters and significance to local maritime routes.
-
A.
Rapadalen
Rapadalen is a renowned, remote river valley in northern Sweden known for its dramatic alpine scenery and rich wildlife within Sarek National Park.
-
B.
Harpefoss
Harpefoss is a small village in Sør-Fron Municipality in Innlandet county, Norway, known for its scenic valley setting along the Gudbrandsdalslågen river.
-
C.
Tallkrogen
Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
-
D.
Follebu
Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
-
E.
Lysthaugen
Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0268608190947a58f559a67717 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8b2ea5c8190b6e5f3fcbd7c265f |
completed | May 9, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_69fefa54397c81909c9bfb8c0553b3d1 |
completed | May 9, 2026, 9:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fefb04d7e4819084ac10e05dccb3e3 |
completed | May 9, 2026, 9:14 a.m. |
Created at: April 10, 2026, 3:17 a.m.