Triple
T18413876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Degerfors Municipality |
E441835
|
entity |
| Predicate | hasPopulationCenter |
P2106
|
FINISHED |
| Object |
Degerfors
Degerfors is a small industrial town in central Sweden, best known for its steel industry and historic football club Degerfors IF.
|
E871152
|
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: Degerfors | Statement: [Degerfors Municipality, hasPopulationCenter, Degerfors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Degerfors Context triple: [Degerfors Municipality, hasPopulationCenter, Degerfors]
-
A.
Bengtsfors
Bengtsfors is a small town in western Sweden known for its lakeside setting, forests, and role as a local administrative and service center.
-
B.
Oskarshamn
Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
-
C.
Karlskoga
Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
-
D.
Fagersta
Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
-
E.
Trollhättan
Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
- 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: Degerfors Triple: [Degerfors Municipality, hasPopulationCenter, Degerfors]
Generated description
Degerfors is a small industrial town in central Sweden, best known for its steel industry and historic football club Degerfors IF.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Degerfors Target entity description: Degerfors is a small industrial town in central Sweden, best known for its steel industry and historic football club Degerfors IF.
-
A.
Bengtsfors
Bengtsfors is a small town in western Sweden known for its lakeside setting, forests, and role as a local administrative and service center.
-
B.
Oskarshamn
Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
-
C.
Karlskoga
Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
-
D.
Fagersta
chosen
Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
-
E.
Trollhättan
Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
- F. None of above.
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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a26d268819098e6791dc98efcda |
completed | April 19, 2026, 6:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a043f1a0f108190a81e26728e367e7e |
completed | May 13, 2026, 9:06 a.m. |
| NEDg | Description generation | batch_6a044044109c8190a767a0ac29a95f53 |
completed | May 13, 2026, 9:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04411b29048190807604f3687a56a0 |
completed | May 13, 2026, 9:15 a.m. |
Created at: April 10, 2026, 10:47 a.m.