Triple
T9828018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eigersund |
E238707
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Helleland
Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
|
E823885
|
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: Helleland | Statement: [Eigersund, hasSettlement, Helleland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helleland Context triple: [Eigersund, hasSettlement, Helleland]
-
A.
Hjelmeland
Hjelmeland is a rural municipality in southwestern Norway known for its fjord landscapes, agriculture, and traditional fruit farming.
-
B.
Mykland
Mykland is a small village in Agder county, Norway, known for its rural setting and surrounding forests and lakes.
-
C.
Hadeland
Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
-
D.
Haugalandet
Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
-
E.
Helgeland
Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
- 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: Helleland Triple: [Eigersund, hasSettlement, Helleland]
Generated description
Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Helleland Target entity description: Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
-
A.
Hjelmeland
Hjelmeland is a rural municipality in southwestern Norway known for its fjord landscapes, agriculture, and traditional fruit farming.
-
B.
Mykland
Mykland is a small village in Agder county, Norway, known for its rural setting and surrounding forests and lakes.
-
C.
Hadeland
Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
-
D.
Haugalandet
Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
-
E.
Helgeland
Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3268fcc8190b7a028f224512e5f |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc8ca2808190a1da0641162f12d1 |
completed | April 5, 2026, 2:44 a.m. |
| NEDg | Description generation | batch_69d1cf8c89f481908dcc9c430d9e45a2 |
completed | April 5, 2026, 2:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d01f546881909e65789ed2895825 |
completed | April 5, 2026, 2:59 a.m. |
Created at: March 30, 2026, 8:32 p.m.