Triple
T17404499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamppi station |
E423176
|
entity |
| Predicate | hasNameInFinnish |
P23453
|
FINISHED |
| Object | Kamppi |
—
|
NE NERFINISHED |
How this triple was built (2 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: Kamppi | Statement: [Kamppi station, hasNameInFinnish, Kamppi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamppi Context triple: [Kamppi station, hasNameInFinnish, Kamppi]
-
A.
Kamppi district
chosen
Kamppi district is a central neighborhood in Helsinki, Finland, known as a major commercial, cultural, and transportation hub of the city.
-
B.
Raasepori
Raasepori is a coastal town and municipality in southern Finland known for its medieval castle ruins and historic wooden town of Ekenäs.
-
C.
Vantaa
Vantaa is a major city in the Helsinki metropolitan area of southern Finland, known for hosting Helsinki Airport and serving as an important commercial and residential hub.
-
D.
Munkkiniemi
Munkkiniemi is a residential district in western Helsinki, Finland, known for its seaside location, parks, and notable architecture.
-
E.
Hietaniemi
Hietaniemi is a district in Helsinki, Finland, known for its seaside location, cemetery, and popular recreational areas including Hietaniemi Beach.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b068248819088871d79f8a38f30 |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:45 a.m.