Triple
T12159003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Finland |
E289654
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Viitasaari
Viitasaari is a town and municipality in the Central Finland region, known for its lakeside landscapes and outdoor recreation opportunities.
|
E967082
|
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: Viitasaari | Statement: [Central Finland, hasMunicipality, Viitasaari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viitasaari Context triple: [Central Finland, hasMunicipality, Viitasaari]
-
A.
Lauttasaari
Lauttasaari is an island district of Helsinki, Finland, known for its residential areas, seaside parks, and easy access to the city center.
-
B.
Pietarsaari
Pietarsaari is a bilingual coastal town in western Finland known for its historic wooden architecture and maritime heritage.
-
C.
Tammisaari
Tammisaari is a historic coastal town in southern Finland, known for its well-preserved wooden old town and seaside setting.
-
D.
Kemiönsaari
Kemiönsaari is a bilingual Finnish municipality and island community known for its coastal archipelago landscapes in Southwest Finland.
-
E.
Siltasaari
Siltasaari is a central district of Helsinki, Finland, known for its urban waterfront setting and role as a key traffic and commercial hub.
- 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: Viitasaari Triple: [Central Finland, hasMunicipality, Viitasaari]
Generated description
Viitasaari is a town and municipality in the Central Finland region, known for its lakeside landscapes and outdoor recreation opportunities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Viitasaari Target entity description: Viitasaari is a town and municipality in the Central Finland region, known for its lakeside landscapes and outdoor recreation opportunities.
-
A.
Lauttasaari
Lauttasaari is an island district of Helsinki, Finland, known for its residential areas, seaside parks, and easy access to the city center.
-
B.
Pietarsaari
Pietarsaari is a bilingual coastal town in western Finland known for its historic wooden architecture and maritime heritage.
-
C.
Tammisaari
Tammisaari is a historic coastal town in southern Finland, known for its well-preserved wooden old town and seaside setting.
-
D.
Kemiönsaari
Kemiönsaari is a bilingual Finnish municipality and island community known for its coastal archipelago landscapes in Southwest Finland.
-
E.
Siltasaari
Siltasaari is a central district of Helsinki, Finland, known for its urban waterfront setting and role as a key traffic and commercial hub.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915c277e481908351bf4e664dda42 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f69e8498819080d571e6fb4edfde |
completed | May 2, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69f601e0777081909e1212436680a10d |
completed | May 2, 2026, 1:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f602a21f948190849839301f49d55a |
completed | May 2, 2026, 1:56 p.m. |
Created at: April 8, 2026, 9:50 p.m.