Triple
T9711035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuortane |
E235022
|
entity |
| Predicate | hasNeighbour |
P5707
|
FINISHED |
| Object |
Alavus
Alavus is a small town and municipality in the South Ostrobothnia region of western Finland, known for its lakes and rural landscapes.
|
E816842
|
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: Alavus | Statement: [Kuortane, hasNeighbour, Alavus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alavus Context triple: [Kuortane, hasNeighbour, Alavus]
-
A.
Vasastan
Vasastan is a central district in Stockholm, Sweden, known for its early 20th-century architecture, lively cafés, and residential character.
-
B.
Taunus region
The Taunus region is a low mountain range in Hesse, Germany, known for its forested hills, spa towns, and historical castles overlooking the Rhine-Main area.
-
C.
Tartumaa
Tartumaa is a historical region in southeastern Estonia centered around the city of Tartu, known for its cultural and educational significance.
-
D.
Merikarvia
Merikarvia is a coastal municipality in western Finland known for its Baltic Sea shoreline, fishing traditions, and natural landscapes.
-
E.
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.
- 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: Alavus Triple: [Kuortane, hasNeighbour, Alavus]
Generated description
Alavus is a small town and municipality in the South Ostrobothnia region of western Finland, known for its lakes and rural landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alavus Target entity description: Alavus is a small town and municipality in the South Ostrobothnia region of western Finland, known for its lakes and rural landscapes.
-
A.
Vasastan
Vasastan is a central district in Stockholm, Sweden, known for its early 20th-century architecture, lively cafés, and residential character.
-
B.
Taunus region
The Taunus region is a low mountain range in Hesse, Germany, known for its forested hills, spa towns, and historical castles overlooking the Rhine-Main area.
-
C.
Tartumaa
Tartumaa is a historical region in southeastern Estonia centered around the city of Tartu, known for its cultural and educational significance.
-
D.
Merikarvia
Merikarvia is a coastal municipality in western Finland known for its Baltic Sea shoreline, fishing traditions, and natural landscapes.
-
E.
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.
- 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_69ca84cd8fa0819090a5e243ceb37003 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e0591208190aa57cc9e2aebafb7 |
completed | April 1, 2026, 10:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19f8876748190b0b5efb12031f532 |
completed | April 4, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69d1a03e88748190b888d6ee2ad2f0f9 |
completed | April 4, 2026, 11:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1a0c05aa88190a93b0b71bef5c417 |
completed | April 4, 2026, 11:37 p.m. |
Created at: March 30, 2026, 8:19 p.m.