Triple
T11359869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helsinki–Riihimäki railway |
E269056
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Järvenpää |
E53754
|
NE FINISHED |
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: Järvenpää | Statement: [Helsinki–Riihimäki railway, serves, Järvenpää]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Järvenpää Context triple: [Helsinki–Riihimäki railway, serves, Järvenpää]
-
A.
Järvenpää
chosen
Järvenpää is a small city in southern Finland known for its lakeside setting and cultural heritage, including its association with composer Jean Sibelius.
-
B.
Nurmijärvi
Nurmijärvi is a municipality in southern Finland known for being one of the largest rural municipalities in the country and part of the Greater Helsinki region.
-
C.
Ylöjärvi
Ylöjärvi is a municipality in the Pirkanmaa region of western Finland, located near the city of Tampere and known for its lakes and natural surroundings.
-
D.
Kankaanpää
Kankaanpää is a small town and municipality in the Satakunta region of western Finland, known for its surrounding forests and lakes.
-
E.
Ruovesi
Ruovesi is a municipality in the Pirkanmaa region of Finland, known for its lakeside landscapes that have inspired Finnish artists and writers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea42fe608190b9c71dd63f8780f3 |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f74602a7ec8190980e5e6a80aa1235 |
completed | May 3, 2026, 12:56 p.m. |
Created at: April 8, 2026, 9:33 p.m.