Triple
T18456270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oulu sub-region |
E450909
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Liminka |
—
|
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: Liminka | Statement: [Oulu sub-region, hasMunicipality, Liminka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liminka Context triple: [Oulu sub-region, hasMunicipality, Liminka]
-
A.
Liminka
chosen
Liminka is a municipality in Northern Ostrobothnia, Finland, known for its rural landscapes and bird-rich Liminka Bay wetland area.
-
B.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
C.
Melinka
Melinka is a small coastal town in southern Chile that serves as the main settlement and administrative center of the remote Guaitecas Archipelago.
-
D.
Timka
Timka is a Russian diminutive form of the male given name Timofey, typically used as an affectionate nickname.
-
E.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5264c10408190b2085ade88655c7d |
completed | April 19, 2026, 7 p.m. |
Created at: April 10, 2026, 11:31 a.m.