Triple
T3522103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oksskolten |
E74445
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Hemnes
Hemnes is a municipality in Nordland county, Norway, known for its mountainous landscapes, fjords, and outdoor recreation opportunities.
|
E382140
|
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: Hemnes | Statement: [Oksskolten, locatedIn, Hemnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hemnes Context triple: [Oksskolten, locatedIn, Hemnes]
-
A.
Tvedestrand
Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
-
B.
Steinkjer
Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
-
C.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
-
D.
Risør
Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
-
E.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
- 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: Hemnes Triple: [Oksskolten, locatedIn, Hemnes]
Generated description
Hemnes is a municipality in Nordland county, Norway, known for its mountainous landscapes, fjords, and outdoor recreation opportunities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hemnes Target entity description: Hemnes is a municipality in Nordland county, Norway, known for its mountainous landscapes, fjords, and outdoor recreation opportunities.
-
A.
Tvedestrand
Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
-
B.
Steinkjer
Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
-
C.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
-
D.
Risør
Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
-
E.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc4dd6d48190a5a3f4b86c82b86c |
completed | March 8, 2026, 6:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4cdd2715c81908250bb2925de8e1f |
completed | March 14, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69b4ce71b9e4819089d4b74cad82fa23 |
completed | March 14, 2026, 2:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4d21472648190a1ef55af8c046182 |
completed | March 14, 2026, 3:12 a.m. |
Created at: March 8, 2026, 3:19 p.m.