Triple
T14469365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. S. Sirén |
E358796
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Ylöjärvi |
—
|
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: Ylöjärvi | Statement: [J. S. Sirén, placeOfBirth, Ylöjärvi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ylöjärvi Context triple: [J. S. Sirén, placeOfBirth, Ylöjärvi]
-
A.
Ylöjärvi
chosen
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.
-
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.
Ruovesi
Ruovesi is a municipality in the Pirkanmaa region of Finland, known for its lakeside landscapes that have inspired Finnish artists and writers.
-
D.
Seinäjoki
Seinäjoki is a city in Southern Ostrobothnia, Finland, known as a regional commercial and cultural center with distinctive modernist architecture by Alvar Aalto.
-
E.
Järvenpää
Järvenpää is a small city in southern Finland known for its lakeside setting and cultural heritage, including its association with composer Jean Sibelius.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f969788190a5114f92d7159aae |
completed | April 14, 2026, 7:14 p.m. |
Created at: April 10, 2026, 1:20 a.m.