Triple
T12000113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Västernorrland County |
E285635
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Timrå
Timrå is a small industrial and coastal locality in northern Sweden, known for its paper and pulp industry and strong ice hockey tradition.
|
E959000
|
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: Timrå | Statement: [Västernorrland County, containsSettlement, Timrå]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timrå Context triple: [Västernorrland County, containsSettlement, Timrå]
-
A.
Skellefteå
Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
-
B.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
C.
Risberg
Risberg is a Swedish surname borne by various notable individuals, including athletes and public figures.
-
D.
Østerås
Østerås is a suburban area in Bærum, Norway, best known as the western endpoint of one of the Oslo Metro lines.
-
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: Timrå Triple: [Västernorrland County, containsSettlement, Timrå]
Generated description
Timrå is a small industrial and coastal locality in northern Sweden, known for its paper and pulp industry and strong ice hockey tradition.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Timrå Target entity description: Timrå is a small industrial and coastal locality in northern Sweden, known for its paper and pulp industry and strong ice hockey tradition.
-
A.
Skellefteå
Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
-
B.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
C.
Risberg
Risberg is a Swedish surname borne by various notable individuals, including athletes and public figures.
-
D.
Østerås
Østerås is a suburban area in Bærum, Norway, best known as the western endpoint of one of the Oslo Metro lines.
-
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
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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c26d7881909b67a31d04882eb5 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f472917ed08190a872d9e5663d5ed5 |
completed | May 1, 2026, 9:29 a.m. |
| NEDg | Description generation | batch_69f47b7e4a40819085680c48eed5418a |
completed | May 1, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f47df40a8c8190bd7350ba27f57214 |
completed | May 1, 2026, 10:18 a.m. |
Created at: April 8, 2026, 9:46 p.m.