Triple
T5707035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sørlandet Line |
E125808
|
entity |
| Predicate | hasMajorCityOnRoute |
P65699
|
FINISHED |
| Object |
Egersund
Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
|
E587421
|
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: Egersund | Statement: [Sørlandet Line, hasMajorCityOnRoute, Egersund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Egersund Context triple: [Sørlandet Line, hasMajorCityOnRoute, Egersund]
-
A.
Kristiansund
Kristiansund is a coastal city in western Norway known for its historic clipfish industry, distinctive layout across several islands, and picturesque harbor.
-
B.
Kristiansand
Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
-
C.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
D.
Farsund
Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
-
E.
Stavanger
Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
- 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: Egersund Triple: [Sørlandet Line, hasMajorCityOnRoute, Egersund]
Generated description
Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Egersund Target entity description: Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
-
A.
Kristiansund
Kristiansund is a coastal city in western Norway known for its historic clipfish industry, distinctive layout across several islands, and picturesque harbor.
-
B.
Kristiansand
Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
-
C.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
D.
Farsund
Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
-
E.
Stavanger
Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0335cf55c8190937a8657406ac4a2 |
completed | March 22, 2026, 6:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62cddd8188190928e01ba450637c2 |
completed | March 27, 2026, 7:08 a.m. |
| NEDg | Description generation | batch_69c62dcb9e1481909fb357f2b010bc19 |
completed | March 27, 2026, 7:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c62e33354481908a6a9af5c245f307 |
completed | March 27, 2026, 7:13 a.m. |
Created at: March 22, 2026, 3:45 p.m.