Triple
T14812246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mülheim an der Ruhr |
E348208
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Kuusankoski
Kuusankoski is a town in southern Finland known historically for its paper industry and location along the Kymijoki River.
|
E1285746
|
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: Kuusankoski | Statement: [Mülheim an der Ruhr, hasTwinTown, Kuusankoski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuusankoski Context triple: [Mülheim an der Ruhr, hasTwinTown, Kuusankoski]
-
A.
Tikkakoski
Tikkakoski is a district in Jyväskylä, Finland, known for its military air base and role as a key center for the Finnish Air Force.
-
B.
Taivalkoski
Taivalkoski is a rural municipality in Northern Ostrobothnia, Finland, known for its forests, lakes, and outdoor recreation opportunities.
-
C.
Valkeakoski
Valkeakoski is a town and municipality in the Pirkanmaa region of southern Finland, known for its paper industry and lakeside setting.
-
D.
Hämeenkoski
Hämeenkoski is a small municipality in southern Finland, historically part of the Häme region and known as the birthplace of former Finnish president Juho Kusti Paasikivi.
-
E.
Kajansi
Kajansi is a township in Uganda located near Kampala, known for its strategic position along the Kampala–Entebbe road and its local market and trading activities.
- 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: Kuusankoski Triple: [Mülheim an der Ruhr, hasTwinTown, Kuusankoski]
Generated description
Kuusankoski is a town in southern Finland known historically for its paper industry and location along the Kymijoki River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kuusankoski Target entity description: Kuusankoski is a town in southern Finland known historically for its paper industry and location along the Kymijoki River.
-
A.
Tikkakoski
Tikkakoski is a district in Jyväskylä, Finland, known for its military air base and role as a key center for the Finnish Air Force.
-
B.
Taivalkoski
Taivalkoski is a rural municipality in Northern Ostrobothnia, Finland, known for its forests, lakes, and outdoor recreation opportunities.
-
C.
Valkeakoski
Valkeakoski is a town and municipality in the Pirkanmaa region of southern Finland, known for its paper industry and lakeside setting.
-
D.
Hämeenkoski
Hämeenkoski is a small municipality in southern Finland, historically part of the Häme region and known as the birthplace of former Finnish president Juho Kusti Paasikivi.
-
E.
Kajansi
Kajansi is a township in Uganda located near Kampala, known for its strategic position along the Kampala–Entebbe road and its local market and trading activities.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decf374f288190aa918b1b6b507420 |
completed | April 14, 2026, 11:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0242d952988190b9b3eaca8fa92431 |
completed | May 11, 2026, 8:58 p.m. |
| NEDg | Description generation | batch_6a0246f31c8c819097685337f0f14dad |
completed | May 11, 2026, 9:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a02478d775c8190ac9d14bd260e7eca |
completed | May 11, 2026, 9:18 p.m. |
Created at: April 10, 2026, 1:47 a.m.