Triple
T13679450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinslaken |
E327959
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Lomma
Lomma is a coastal municipality in southern Sweden known for its beaches and proximity to the city of Malmö.
|
E1055490
|
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: Lomma | Statement: [Dinslaken, hasTwinTown, Lomma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lomma Context triple: [Dinslaken, hasTwinTown, Lomma]
-
A.
Lomme
Lomme is a suburban district and former commune that now forms part of the metropolitan area of Lille in northern France.
-
B.
Tammela
Tammela is a rural municipality in southern Finland known for its forests, lakes, and national parks such as Torronsuo and Liesjärvi.
-
C.
Lapua
Lapua is a small town in western Finland known for its historical significance, including a former state cartridge factory and its role in the Lapua Movement.
-
D.
Sastamala
Sastamala is a town and municipality in southwestern Finland known for its historical churches, cultural heritage, and scenic lakeside landscapes.
-
E.
Loimaa
Loimaa is a town and municipality in southwestern Finland known for its agricultural surroundings and small-town character.
- 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: Lomma Triple: [Dinslaken, hasTwinTown, Lomma]
Generated description
Lomma is a coastal municipality in southern Sweden known for its beaches and proximity to the city of Malmö.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lomma Target entity description: Lomma is a coastal municipality in southern Sweden known for its beaches and proximity to the city of Malmö.
-
A.
Lomme
Lomme is a suburban district and former commune that now forms part of the metropolitan area of Lille in northern France.
-
B.
Tammela
Tammela is a rural municipality in southern Finland known for its forests, lakes, and national parks such as Torronsuo and Liesjärvi.
-
C.
Lapua
Lapua is a small town in western Finland known for its historical significance, including a former state cartridge factory and its role in the Lapua Movement.
-
D.
Sastamala
Sastamala is a town and municipality in southwestern Finland known for its historical churches, cultural heritage, and scenic lakeside landscapes.
-
E.
Loimaa
Loimaa is a town and municipality in southwestern Finland known for its agricultural surroundings and small-town character.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc66cbb088190907cb89dda8e4ebd |
completed | April 12, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944347a08190bc1386e78ddb3e71 |
completed | May 3, 2026, 6:30 p.m. |
| NEDg | Description generation | batch_69f79523bf608190addeca563bea132e |
completed | May 3, 2026, 6:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7965cc9f88190acbf232615a9e87b |
completed | May 3, 2026, 6:39 p.m. |
Created at: April 9, 2026, 9:53 p.m.