Triple
T17657867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurum |
E440171
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Rødtangen
Rødtangen is a small coastal village and recreational area in Hurum, Norway, known for its beaches and scenic views along the Oslofjord.
|
E1281743
|
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: Rødtangen | Statement: [Hurum, contains, Rødtangen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rødtangen Context triple: [Hurum, contains, Rødtangen]
-
A.
Bergneset
Bergneset is a coastal headland in Antarctica located near Hope Bay on the Trinity Peninsula.
-
B.
Sørenga
Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
-
C.
Røssåga
Røssåga is a river in Nordland county, Norway, known for flowing through Rana Municipality and being utilized for hydroelectric power production.
-
D.
Nesoddtangen
Nesoddtangen is a village and administrative center in Nesodden municipality in Viken county, Norway, located on a peninsula directly across the Oslofjord from central Oslo.
-
E.
Strynø
Strynø is a small Danish island in the Baltic Sea known for its rural charm, traditional village environment, and location between the larger islands of Langeland and Ærø.
- 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: Rødtangen Triple: [Hurum, contains, Rødtangen]
Generated description
Rødtangen is a small coastal village and recreational area in Hurum, Norway, known for its beaches and scenic views along the Oslofjord.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rødtangen Target entity description: Rødtangen is a small coastal village and recreational area in Hurum, Norway, known for its beaches and scenic views along the Oslofjord.
-
A.
Bergneset
Bergneset is a coastal headland in Antarctica located near Hope Bay on the Trinity Peninsula.
-
B.
Sørenga
Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
-
C.
Røssåga
Røssåga is a river in Nordland county, Norway, known for flowing through Rana Municipality and being utilized for hydroelectric power production.
-
D.
Nesoddtangen
Nesoddtangen is a village and administrative center in Nesodden municipality in Viken county, Norway, located on a peninsula directly across the Oslofjord from central Oslo.
-
E.
Strynø
Strynø is a small Danish island in the Baltic Sea known for its rural charm, traditional village environment, and location between the larger islands of Langeland and Ærø.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea3b4cc81908eec7032cf221d49 |
completed | April 19, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02232075b48190a3defc74027b775e |
completed | May 11, 2026, 6:42 p.m. |
| NEDg | Description generation | batch_6a02258632d081909249af799f8d2adb |
completed | May 11, 2026, 6:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0225cb32c4819089ef592279cd64cb |
completed | May 11, 2026, 6:54 p.m. |
Created at: April 10, 2026, 9:28 a.m.